American school districts access an average of 2,982 distinct edtech tools per year. Across the Pacific pond, Singapore has a single Student Learning Space platform with a curated list of third party apps that follows national standards. Estonia, famous for its digital government including ed tech, ranks 1st in Europe according to the 2022 PISA assessment and consistently ranks among Europe’s top performers.

That’s not a typo. Nearly three thousand tools per district. Individual teachers navigate about 42 different platforms annually. Two-thirds of purchased software licenses go unused. Specifically, 67 percent of software licenses were found to be unused, with some cases reaching as high as 90 percent.

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One of the (predictably) standard explanations is teacher training. Teachers don’t know how to use what they’re given. And that’s true, but it’s the wrong frame. You can’t train anyone effectively when you’re managing three thousand tools.

The underlying problem is implementation capacity: can your institution pick something, train people on it, and stick with it? This isn’t about funding or technical expertise, though both matter. It’s about institutional follow-through. The ability to make a decision and then actually execute it across an organization, for years.

Here’s what I keep coming back to: Singapore and Estonia didn’t develop implementation capacity by building good edtech systems. They built good edtech systems because they already had it. Both countries achieved exceptional educational results long before their current platforms existed. The technology reveals their institutional competence. It didn’t create it.

This capacity can exist in American institutions. The Department of Defense runs 161 schools worldwide for military families, all under centralized civilian control. They can standardize. They can train systematically. They can sustain decisions over time. Most American states and districts, with vanishingly few exceptions, cannot.

Which raises an uncomfortable question: if the problem isn’t funding, and it isn’t training, and it isn’t technology, if it’s the basic ability to implement anything coherently, then what exactly is our theory of change?

The Three Models

Singapore’s Ministry of Education didn’t purchase software from vendors. It built the Student Learning Space from the ground up, starting in 2016, working with a domestic technology company and GovTech Singapore. The government owns the platform. It controls the roadmap, the data architecture, the integration decisions. When MOE wanted AI capabilities for lesson planning, it embedded them directly into SLS rather than buying separate tools. The platform now serves about 500,000 users with curriculum-aligned resources from primary school through pre-university.

MOE has whitelisted external tools for integration, but on its terms, not vendors’. Every teacher receives 100 hours of professional development annually, and that training can be platform-specific because there’s only one platform to master.

Estonia took a different path to the same outcome. Two private platforms, eKool and Stuudium, cover 95% of Estonian schools. The government doesn’t own them. But it controls something more important: the standards. All educational systems connect through X-Road, Estonia’s national data exchange layer (ie the quick explanation it is a set of standards, systems, and software to share data between government and approved third parties and it is not blockchain) . Every student has a secure auth account providing access to all educational resources. Private platforms must comply with interoperability requirements to participate.

This solves a problem Americans rightly worry about: vendor lock-in. If eKool raised prices dramatically or degraded service, schools could migrate to Stuudium without losing their data or retraining on entirely foreign systems. The government controls the standards layer; vendors compete within those standards.

Both countries achieved exceptional educational results long before these systems existed. Singapore ranked among the world’s best on international assessments for decades before SLS launched. Estonia has performed at or near the top of European PISA rankings since 2006, when eKool was four years old and X-Road was still being developed. The National Institute of Education has trained Singaporean teachers through rigorous, centralized programs since 1991. Estonia’s ProgeTiger program has trained over 4,000 teachers, and nearly all schools participate. These countries built effective educational technology because they already knew how to build effective anything.

Now look at the United States.

We are aware that districts accessed an average of 2,982 distinct edtech tools in 2024-25. That’s up from 895 in 2018-19. A 3x increase in eight years. The market includes over 10,000 tracked products.

The learning management system market alone fragments among Canvas (about 28% market share), Google Classroom (24%), Schoology (22%), Moodle (7% and declining), and a long tail of others. Student information systems are rarely integrated with instructional tools. The EdTech Top 40 includes products from dozens of vendors across every category, and the list changes annually as tools gain and lose favor.

Here’s where it gets grim. Glimpse K12 analyzed $2 billion in school spending and found that 67% of educational software licenses go unused. In some districts, up to 90% sit idle. The Overdeck Family Foundation estimates only 5% of edtech tools are used at the dosage required to produce measurable impact.

We have ten times more tools than we did eight years ago. Two-thirds of them collect dust. One in twenty gets used enough to matter.

Why Teacher Training Cannot Fix (System) Problems

The training explanation is seductive because it offers a tractable solution: spend more on professional development. Districts already do. According to analysis from the Research Partnership for Professional Learning at Brown University’s Annenberg Institute, US districts spent an average of $8,300 per teacher on professional development in 2022, up from $6,250 in 2001. TNTP’s widely cited 2015 “Mirage” study found three large districts spending about $18,000 per teacher annually. National estimates reach $18 billion in total. (Harvard’s Heather Hill has criticized the TNTP methodology for inflating expenditure by including salary increases from credentials, so the true figure is contested. But even lower estimates represent substantial investment.)

What do we get for this?

TNTP found that only 3 in 10 teachers improved over a two-to-three-year period after participating in professional development. Two in 10 actually got worse. The researchers “found no evidence that any particular kind or amount of professional development consistently helps teachers improve.” Teachers spent an average of 19 school days per year, nearly 10% of instructional time, in training that produced no measurable benefit.

Using LLMs (or AI) in teaching is a new field with questionable results, but how countries preparing for it paint a picture. The OECD’s TALIS 2024 survey, covering 280,000 educators across 55 systems, offers a comparison. On artificial intelligence: 76% of Singapore teachers received AI training, and 75% use AI in teaching. In France, 9% received training and 14% use AI.

The OECD found that “teachers are not using artificial intelligence independently. Rather, education systems are providing guidance on how the technology can be used productively and safely.” Singapore’s teachers have 100 hours of annual professional development. Those hours go toward mastering one platform they’ll use throughout their careers.

American teachers get training too. But a teacher who masters Canvas in one district may move to a district using Moodle or another with Google Classroom. Training hours that could build genuine expertise instead become introduction after introduction to tools that teachers will soon abandon.

A Common Sense Media survey found that 31% of educators cannot use technology because they lack training, and 63% said district communication about available edtech is “moderate or non-existent.” Even when training happens, it doesn’t stick. Cambridge University researchers documented what happened when a large district near Washington DC had to abandon a major platform during COVID-19: “Years of professional development were lost as teachers were forced to switch to new or alternative platforms within a matter of days.”

The Shadow IT Question

There’s a defense of the American approach: maybe the proliferation of tools reflects teacher initiative. Educators finding what works for their students rather than accepting top-down mandates. Thousands of tools as healthy experimentation.

There’s something to this. Anyone who’s worked in enterprise software recognizes the pattern. Shadow IT is technology adopted outside official channels, and it emerges in every organization where the official systems fail to meet real needs. Employees use Dropbox when the approved file-sharing system is clunky. Teams adopt Slack (or even Discord!) when the company mandates something worse (like post 2024 Microsoft Teams).

Good CTOs (should) pay attention to shadow IT because it’s signal, but most CTOs still treat it as noise. It tells you what users actually need. But it also tells you something else: top-down standardization doesn’t work when the standard is bad. You can mandate a tool. You can’t mandate that people use it well, or use it at all. The 67% unused license rate is what happens when procurement runs ahead of actual needs. Centralizing decisions doesn’t help if the decisions are wrong.

Teachers who install Kahoot or Blooket on their own are solving problems that centralized procurement hasn’t addressed. There’s real value in teachers having flexibility to find tools suited to their specific contexts.

But the evidence suggests the experimentation defense doesn’t hold for American edtech. Districts aren’t rejecting official tools in favor of better alternatives discovered through grassroots innovation. The proliferation comes from vendor marketing and conference demos, purchasing processes disconnected from actual classroom needs. Teachers aren’t experimenting. Procurement departments are shopping.

Shadow IT is a symptom of implementation failure. When teachers have to work around official systems, the official systems aren’t working. Singapore teachers don’t need shadow IT because SLS meets their needs. The platform evolved from teacher feedback, not despite it. Teachers should have agency. The question is whether the system channels that agency productively or dissipates it across three thousand tools.

State Consolidation: Necessary but Risky

At least 13 states have implemented statewide LMS contracts with Canvas. Several, notably Utah and Wyoming, have achieved K-12 through college continuity.

Utah is the clearest success. After a RFP process in 2010, the Utah Education Network selected Canvas for statewide programs. By 2018, 38 of 41 districts had adopted the platform. The legislature funds Canvas licensing as an ongoing appropriation, with districts paying only a one-time $2,500 implementation fee. UEN uses Canvas to provide online professional development to more than 3,500 Utah teachers annually.

Wyoming’s statewide K-20 contract reduced per-student costs from over $25 in some districts to under $4, with estimated annual savings of $250,000. When COVID-19 struck, the prior investment paid immediate dividends. A technology director reported that Canvas usage “shot up to nearly all staff members” within a week.

Other states achieved similar results through regional cooperatives rather than state contracts. Texas’s TEKS Resource System operates through a shared service agreement among all 20 Education Service Centers, with over 90% of districts participating. New York’s Boards of Cooperative Educational Services, created in 1948, operates 37 regional bodies serving nearly all districts outside the five largest cities. The Regional Information Centers within BOCES support more than 95% of public school districts and negotiate contracts collectively.

But consolidation carries risks that Estonia’s model avoids. When Utah standardizes on Canvas, it becomes dependent on Instructure. If Instructure raises prices, degrades service, or gets acquired by a private equity firm with different priorities, Utah has limited options. Years of training, content development, and workflow integration create switching costs that vendors can exploit. The same consolidation that enables coherent training also creates vendor lock-in.

Fragmentation is worse. But this shows what’s missing: interoperability standards. Utah has a statewide platform but no state-mandated data portability requirements. If Utah wanted to switch from Canvas to another LMS, migrating course content, assessment data, and integration configurations would be enormously costly. Estonia’s X-Road architecture makes such transitions feasible. American states have no equivalent.

And consolidation doesn’t guarantee adoption. New Mexico contracted with Desire2Learn as its statewide LMS. But data showed “there wasn’t a strong correlation between the state contract and what districts were actually using.” Many districts adopted Canvas instead.

This is a prime (but certainly not the only) example of shadow IT in education. You can mandate a platform. You can’t mandate that districts use it, especially when they’ve already invested in something else. Contracts without mandates or strong incentives don’t drive adoption. Districts with existing platforms and trained staff resist switching even when alternatives are free. The same dynamic that plays out with individual teachers working around clunky official systems plays out at the organizational level.

Nobody has measured whether consolidated states actually achieve better utilization or outcomes than fragmented ones. The data doesn’t exist.

And platform standardization solves only one dimension of the problem. Utah has one LMS. It doesn’t have the training program or standards as Singapore. There’s no EdTech Masterplan (among other education plans) with explicit strategic priorities and dedicated implementation divisions. Consolidation purchasing power and big tech decisions is necessary. It isn’t sufficient and if treated as the end all be all like New Mexico did, it will backfire.

The Administrator Training Void

We’ve focused on teacher training. But teachers don’t make purchasing decisions. Administrators do.

Singapore explicitly incorporates school leaders into its capacity-building framework. The Leaders in Education Programme is a six-month, full-time program at the National Institute of Education preparing vice-principals and ministry officers for principalship. Participants are removed from their positions for half a year. The program uses the 5R5M framework covering five roles of school leadership, and the Learning Partnership in Educational Technology Branch explicitly builds capacity among “teachers, middle managers and school leaders.”

Teachers get 100 hours of annual training on one platform. Principals train on the same platform. Even if Singapore decided to swap out SLS with another platform, they understand what tools that the Ministry of Education uses and the kind of capabilities they could expect. They can support implementation. They can evaluate whether it’s working. The people making decisions and the people using the tools share a common foundation.

There are virtually no mandatory technology training requirements for US principals and superintendents. The ISTE Standards for Education Leaders exist but aren’t required anywhere. The Consortium for School Networking offers a Certified Education Technology Leader certification, but only about 900 individuals have earned it since the program’s inception. There are roughly 100,000 superintendents and principals nationally.

So untrained administrators make purchasing decisions. Research on edtech procurement found that districts buy products based on vendor marketing and conference demonstrations rather than evidence. The CEO of Teaching Lab observed: “The incentives in the market are kind of messed up, so that you’re not always incentivized to do that type of work” of ensuring teachers actually want and can use products.

This closes the loop on the dysfunction. Teachers get trained on tools they’ll soon abandon. Administrators who’ve never been trained on anything make the buying decisions. Procurement runs on vendor pitches and conference buzz. Districts end up with thousands of all sort of programs, ~two-thirds of which go unused. Teachers route around the official systems that don’t meet their needs. And the cycle continues.

The DoDEA exception

The Department of Defense Education Activity operates 161 schools worldwide serving about 67,000 students. DoDEA’s 2024 NAEP scores exceeded national public school averages by 14 to 25 points across all tested subjects and grades. A 2022 GAO report confirmed that DoDEA’s fourth-grade math and reading scores were higher than 98% and 100% of states, respectively, over the past decade. The New York Times noted that DoDEA campuses “quietly achieve results most educators can only dream of.” It’s the closest thing an “American Singapore” school district as we can get.

DoDEA uses Schoology as its learning management system across all schools, particularly for its Virtual High School program. Additionally, Google Classroom is available alongside Schoology to support virtual learning environments, assignments management, and communication with classroom teachers. Many brick-and-mortar schools use Google Classroom for daily instruction.

All students have DoDEA Google accounts (@student.dodea.edu) for unified identity management, which integrate with ClassLink’s single sign-on solution to access hundreds of digital resources. The organization has a Digital and Virtual Learning Division and a strategic plan that explicitly prioritizes technology modernization and AI integration, including “modernizing its approach to artificial intelligence and technology, ensuring that students and staff can navigate and lead within a digital world.”

But the most telling comparison isn’t test scores. It’s Common Core.

DoDEA schools use Common Core standards. The same standards that generated enormous political controversy across American states. Many states adopted Common Core on paper, then struggled with rollout: inadequate teacher training, misaligned assessments, textbook delays, political backlash. Several states eventually rebranded or abandoned the standards entirely.

DoDEA faced none of these problems. It adopted Common Core, trained teachers coherently, aligned curriculum and assessment, and produced NAEP scores exceeding nearly every state in the nation.

The standards were the same. The implementation was clearly not.

The natural response to the Singapore and Estonia comparisons: why not just adopt their curriculum or license their platforms? Why not have a national curriculum (despite America’s failure with Common Core)? Because adoption isn’t implementation. American education has shown repeatedly that it can adopt reforms while failing to implement them. The machinery that translates policy into classroom practice is broken. Importing Singapore’s curriculum into a system that couldn’t implement Common Core would produce Common Core results: uneven, politicized, disappointing.

Contextual Advantages

DoDEA has advantages beyond consolidation. Military families have employed parents and relatively stable household structures. The schools are well-funded and socioeconomically integrated, even thought military families tend to be lower income and have a history of mental health issues.

But that centralized structure is the point. DoDEA possesses the capacity to standardize, and that capacity extends far beyond technology. It can set curriculum, train teachers coherently, hold schools accountable, and sustain strategic priorities over time. Technology standardization and successful Common Core implementation both flow from broader institutional competence.

DoDEA operates on American soil, employs American educators, and serves American children. The barriers preventing state systems from developing similar capacity are political and institutional, not cultural or intrinsic.

Building the capacity we lack

American states and districts lack the implementation capacity of Singapore or Estonia. They’re unlikely to develop Singapore-style comprehensive state capacity anytime soon. That would require political and institutional transformations far beyond education policy. But implementation capacity isn’t binary. It can be built incrementally, domain by domain.

Educational technology could be a training ground.

State education agencies and large districts already make technology decisions. They negotiate with vendors, write contracts, manage rollouts, coordinate training, evaluate results. They do these things poorly, for the most part. But they do them. The institutional muscles exist in atrophied form.

Building implementation capacity doesn’t require states to develop their own platforms. That would be a mistake. Software development isn’t their comparative advantage, and failed government IT projects litter the landscape. What they need is the capacity to procure well, implement coherently, and hold vendors accountable. These are different skills from building technology. They’re also more achievable.

The states with consolidated LMS contracts have taken a first step. Utah and Virginia showed that statewide coordination is possible. Texas and New York showed that regional intermediaries can aggregate demand and reduce transaction costs. These aren’t Singapore-level achievements, but they represent real institutional learning.

The next step would be building on these foundations: adding interoperability requirements to prevent vendor lock-in, developing serious administrator training programs, creating feedback loops between utilization data and procurement decisions. This isn’t a quick fix. Building institutional capacity takes years, and American political cycles create constant pressure to abandon long-term investments for short-term wins. But it’s more tractable than waiting for comprehensive state capacity to emerge from nowhere.

EdTech is also, in some ways, a forgiving domain for learning. The stakes are lower than infrastructure or healthcare. Failed implementations are costly but not catastrophic. The feedback loops are relatively fast. You can see within a year or two whether teachers are using what you bought.

My Point Being

This isn’t primarily an edtech problem.

The United States has spent decades and billions of dollars on educational technology with remarkably little to show for it. The explanation isn’t bad technology, or bad teachers, or insufficient training budgets. The explanation is that our governance structures lack the capacity to implement coherent systems.

That same implementation deficit appears across American public services. We struggle to build infrastructure, permit housing, reform policing, execute industrial policy. Fragmented authority, inadequate administrative capacity, weak feedback loops. Systems that can’t learn or adapt.

If you care about educational technology working, you have to care about implementation capacity. And if you care about implementation capacity, you have to care about governance. The tools exist. The knowledge exists. The money exists. What doesn’t exist, outside of isolated exceptions like DoDEA, is the institutional machinery to put them together.

But institutional capacity can be built. It has been built, in pockets, even within American education. The question is whether we can learn from those pockets, and from the Singapores and Estonias, to develop the competencies we lack.

EdTech may seem like a small place to start. It might be the right one for a number of districts.

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A nursing graduate from a community college earns the same as one from a traditional university. A computer science graduate from a community college earns $30,000 less.

Both hold bachelor’s degrees. Both attended the same type of institution. The labour market treats them very differently.

This is the finding of a new working paper (Community College Bachelor’s Degrees: How CCB Graduates’ Earnings Compare to AAs and BAs) by Riley Acton, Camila Morales, Kalena Cortes, Julia Turner, and Lois Miller. It is the first national study of community college baccalaureate (CCB) outcomes, covering 13 states and tracking graduates into the labor market. For governors and mayors investing in these programmes, the results suggest that field selection matters more than they may have assumed.

The (Policy) Context

At the time of the writing, Twenty-four US states now allow community colleges to grant bachelor’s degrees. The number awarded quadrupled between 2004 and 2022, from 3,300 to over 16,000. Illinois and Iowa are considering joining this year.

The attraction for state officials is straightforward. Texas will face a shortage of more than 57,000 full-time registered nurses by 2032, according to the Texas Hospital Association. Florida started the 2023 school year with roughly 8,000 teacher vacancies, according to the Florida Education Association. Traditional universities produce graduates, but capacity constraints bite: clinical placements are limited, faculty lines take years to fill, new construction requires legislative appropriations that may not arrive before the next election.

Community colleges offer an alternative. The average CCB costs $16,800 in tuition and fees; a bachelor’s from a traditional public university costs $31,000. The American Association of Community Colleges counts 1,167 public and independent community colleges across the country, rising to 1,600 when branch campuses are included. California alone operates 116 campuses. Many already run associate-degree programmes in nursing, education, and technical fields. Upgrading to bachelor’s programmes means extending existing capacity, not building from scratch.

This is the reuse opportunity. The infrastructure exists. Whether it can be repurposed effectively depends on which programmes states choose to expand.

What the Research Found

The researchers used Census Bureau employment records covering 96% of US jobs, tracking graduates one year after completion. They compared earnings within the same field, isolating institution type.

Nursing CCB graduates earn at parity with traditional university graduates. Criminal justice CCB graduates earn more than their four-year peers. Healthcare and business show no significant penalty.

Computer and information technology diverges sharply. The median CCB graduate earns $30,000 less than a peer from a four-year university. Engineering technology shows penalties of $5,000 to $10,000. Agriculture and liberal arts show smaller but persistent gaps.

The estimates control for graduation year and compare graduates in the same state and field. The pattern is consistent across the dataset.

The study captures only short-term earnings, one year post-graduation. Students choosing CCBs may differ from university students in ways the data cannot observe. The researchers are conducting a resume audit study that may sharpen the causal picture. But the consistency across fields and states is hard to explain away as selection alone.

Understanding How It Works

The paper attributes the divergence to industry alignment.

Nursing graduates follow a narrow path. They take the NCLEX, obtain a licence, and work in healthcare. Seventy-three percent of health professions CCB graduates end up in healthcare and social assistance. Employers know what the credential certifies. The institution that granted it is secondary to whether the graduate passed the boards.

Education follows a similar structure. Seventy-eight percent of education CCB graduates work in educational services. State certification defines the entry route.

Computer science lacks any equivalent pathway. Graduates disperse across finance, healthcare, manufacturing, government, defence, startups. Only 12% end up in professional and technical services, the category containing most technology firms. When employers cannot predict where graduates will land, they use proxies: university reputation, selectivity, the assumption that a four-year institution filtered for quality.

Tight alignment between field and industry correlates with small or no CCB penalties. Diffuse pathways correlate with large ones.

Community Colleges are Supply-Side Policy

This finding reframes what CCBs can do for states.

Most industrial policy focuses on demand: tax incentives to attract firms, infrastructure to support investment, regulatory changes to encourage hiring. These interventions assume workers with the requisite skills exist. Often they do not. A semiconductor fabrication plant means nothing without technicians. A hospital expansion fails if there are no nurses to staff it.

CCBs are a supply-side tool. They produce credentialed workers at lower cost than universities, distributed across regions that four-year institutions do not serve. Roughly 75% of CCB graduates work in the same state where they earned their credential. For fields where the credential performs at parity with a traditional degree, CCBs offer workforce capacity that scales without new campus construction.

The question is which fields qualify.

Why Nursing Works

Nursing CCBs did not succeed by accident. The field accumulated decades of institutional scaffolding before community colleges began offering bachelor’s degrees.

Licensure boards set standards. The NCLEX examination provides a national competency benchmark. Clinical placements during the degree programme create direct hiring pipelines. Hospitals have employed associate-degree nurses for decades and supported their completion of bachelor’s degrees while working. Community college nursing credentials are familiar to employers, not suspect.

Most community colleges already have nursing programmes. They have simulation labs and clinical partnerships with regional hospitals. Faculty have worked the floors. Extending to a bachelor’s programme adds upper-division coursework and expands clinical placements. It does not require building from nothing.

Education has parallel structures: state certification examinations, defined career ladders, employers accustomed to associate-degree holders. Criminal justice and allied health fields share similar characteristics.

Computer science has no licensure board, no national examination, no clinical equivalent. Employers hiring software engineers cannot rely on a credential to signal competence. They rely on institution name instead.

Nursing Is A Template

The nursing model is not a ceiling on what CCBs can accomplish. It is a template.

States wanting to expand CCBs into fields that currently underperform would need to build equivalent infrastructure. Consider cybersecurity. The Bureau of Labor Statistics projects 33% growth in information security analyst positions from 2023 to 2033. A generic computer science CCB will likely replicate the $30,000 penalty: graduates competing against four-year peers for diffuse roles, employers defaulting to institutional signals.

A (theoretical) cybersecurity program designed like nursing might perform differently. That would mean identifying employers with defined hiring needs before launching the programme: regional banks, hospital systems, state agencies, defence contractors. It would mean establishing internship pipelines and hiring commitments. Industry-recognised certifications would need to be layered onto the degree (CompTIA Security+, CISSP, or state-specific credentials). The programme would target specific roles rather than a generic field.

Community colleges adapt quickly when industry demand is clear. The paper notes cannabis science programmes appearing within months of state legalisation. CCBs extend this responsiveness to bachelor’s-level credentials. Whether states will invest in building pathways for higher-stakes fields, rather than simply authorising programmes, is a different question.

The Local Angle

For mayors, CCBs address a problem universities cannot solve: talent retention.

A city of 80,000 without a four-year campus exports its young people. They leave for college and settle where they graduate. The community college has always been there, but until recently could not offer a bachelor’s degree.

The 75% in-state employment rate for CCB graduates likely understates local retention for programmes with strong employer ties. A nursing CCB feeds graduates to the regional hospital. An education CCB feeds them to local school districts. Young people who might otherwise have left can build careers without relocating.

Mayors considering CCB expansion should ask whether local employers will commit to hiring graduates. A nursing programme makes sense if the hospital will participate. A cybersecurity programme makes sense if regional employers have those positions and will help design the pipeline. Absent employer commitment, a programme is a gamble on credentials the local labour market may not value.

State Capacity (As Always) is the Binding Constraint

Authorising CCBs is easy. Building the ecosystems that make them work is harder.

Again, Nursing CCBs succeed because the scaffolding was constructed over decades by licensure boards, professional associations, and healthcare employers. States expanding nursing programmes are leveraging infrastructure they did not have to build.

Expanding into new fields requires states to do the construction themselves: convene employers, negotiate hiring commitments, establish certification standards, design curricula around specific roles. This is workforce development as infrastructure project, not as programme authorisation.

States that treat CCB authorisation as sufficient will see graduates in new fields facing the penalties the current data reveal. States that pair authorisation with deliberate ecosystem construction may achieve different outcomes (not just for students). The mechanism the paper identifies points toward what would need to happen.

Wrapping up

For fields where credentialing infrastructure exists, CCB expansion carries modest risk. Nursing, education, criminal justice, and allied health programmes can be upgraded using existing foundations. Employers know what to expect.

For fields lacking such infrastructure, authorisation alone will not suffice. States would need employer commitments, industry certifications, and defined hiring pipelines before launching programmes. Reluctance from employers to commit signals something about likely outcomes.

Community colleges have the physical capacity. Classrooms, faculty, students: all present. The constraint is not infrastructure but institutional scaffolding, the apparatus that makes a credential legible to employers. Where that scaffolding exists, CCBs work. Where it does not, states face a choice: build it, or accept that the programmes will underperform.

Workforce shortages are a policy problem. CCBs are one tool for addressing them. The research clarifies which applications of the tool are likely to succeed and what would need to change for others to follow.

In “Developing Implementation & Scaling Capacity in Education,” Dean L. Fixsen, Caryn S. Ward, and Karen A. Blase document a decade working with 10 states to build implementation capacity - the organizational infrastructure needed to support sustained education reform. They measured progress repeatedly and documented what worked.

If implementation capacity can be systematically built, it could explain why some reforms succeed while others with identical policies fail.

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Active Implementation Research Network (AIRN) worked with states in two phases using “usability testing” - work with a small group, identify problems, refine the approach, test with the next group. Straight from Deming’s Plan-Do-Study-Act cycle, originally developed for industrial quality control.

Study 1 (2007-2012): Five states

• All started at 0-40% implementation capacity

• Two quit after 20-23 months

• One stayed under 20% for five years

• Two reached 60-70% capacity after five years

Study 2 (2014-2017): Five states with refined approach

• All reached 60-75% capacity within 24 months

• More consistent progress across different contexts

• One ended after 26 months due to leadership change

The intervention involved building implementation teams at state, regional, and district levels. Monthly 2-3 day site visits. Sustained coaching. Twice-yearly capacity assessments.

They measured progress using a State Capacity Assessment (SCA) tracking three areas:

• SMT Investment: Leadership commitment, coordination, resources

• System Alignment: Official guidance documents, design team functioning

• Commitment to Regional Implementation: Resources and support for regional teams

Scores range from 0% (nothing in place) to 100% (everything fully implemented). Benchmarks at 60% for “acquisition” and 80% for “proficiency” based on recommendations from fidelity assessment research.

The Core Idea: From Ghost Systems to Host Systems

The paper frames education reform around a useful concept: most systems are “ghost systems.”

Ghost system: Official policies exist but aren’t actually implemented. You have policies requiring evidence-based reading instruction, teachers get one-day workshops and no ongoing support. Standards exist on paper, infrastructure doesn’t.

Host system: Infrastructure exists to actually implement what policies say should happen. Literacy coaches in schools. Sustained training programs. Regular assessment and adjustment. The organizational capacity to do what you say you’re doing.

The researchers argue most education systems are ghost systems. They tried to build host systems.

This reframes the Mississippi question. Not just whether Mississippi used better reading practices (phonics vs whole language). Whether Mississippi built a host system that could actually implement practices with fidelity while other states remained ghost systems with policies on paper.

The complexity science angle:

The paper roots this in complexity theory: “Systems need internal flexibility to match external complexity.”

Meaning: 14,000 school districts across 50 states, each with different histories, politics, demographics, resources. A centralized mandated solution (like Common Core) can’t adapt to all that variation. But a system of linked teams that can respond to local conditions while maintaining coherent structure theoretically can.

If this theory is right, it (partially) explains why standardized reforms fail. Not because the practices are wrong, but because complex systems can’t implement standardized solutions without the local infrastructure to even adopt it.

What Failed, What Worked, and Why the Sequence Matters

The paper provides specific failure patterns from Study 1:

State #1 (stayed under 20% for 5 years):

• State Transformation Specialists employed outside the education system

• No access to internal communications or meetings

• No authority to call meetings or approach units independently

• Consultants without actual power

States #2 and #3 (quit after 20-23 months):

• “Little or no access” to State Management Team (superintendent and cabinet)

• Specialists segregated in particular units (Special Education, turnaround division)

• Limited collaboration across the broader system

• Isolated specialists without executive support

States #4 and #5 (reached 60-70% but took 5 years):

• “Loosely configured regional groups” with “no meaningful role in supporting programs”

• Only developed functional regional agencies in years 4-5

• No middle layer between state and district

The Study 2 adjustments based on these failures:

Made executive commitment a precondition. Required monthly meetings with superintendent and cabinet before starting work.

Required specialists be full-time state employees in the superintendent’s office with access to all internal systems. No external consultants, no segregated units.

Verified functional regional agencies existed and were willing to participate. Turned away two interested states without viable regional infrastructure (possible selection bias!).

Shifted to “just enough, just in time” teaching methods instead of comprehensive front-loaded training.

The results: All five Study 2 states reached 60%+ capacity within 24 months versus the 5-year timeline in Study 1.

What data shows about sequencing:

Looking at how capacity develops in Study 2:

State #9 trajectory:

• Month 5: Leadership 46%, System Alignment 20%, Regional 0%

• Month 13: Leadership 100%, System Alignment 50%, Regional 25%

• Month 22: Leadership 88%, System Alignment 40%, Regional 69%

Notice the sequence: Leadership commitment enables regional development, which eventually enables system-wide alignment.

This makes sense when you think about what each measures:

Leadership investment includes: Does the management team meet regularly? Do they provide resources? Do State Transformation Specialists have executive access? This can happen quickly once committed.

Regional commitment includes: Are regions allocated staff time? Do they have implementation teams? This requires negotiating with separate agencies and reallocating resources.

System alignment includes: Does the state have written guidance documents describing implementation supports? Do official policies require regional agencies to provide implementation support to districts? Policy changes applying statewide, beyond the transformation zone.

If this sequence holds across contexts, and Study 2 suggests it might, you can’t skip steps. You need executive commitment before you can build regional capacity. You need regional capacity before you can align system-wide policies.

The Transformation Zone Strategy

Rather than attempting statewide change immediately, they start with a “transformation zone” - a vertical slice from classroom to capitol:

• State leaders and staff

• Three regions

• Three districts per region

• Three schools per district

• All teachers and students in participating schools

Why three? The paper gives us an example “Three factorial (3!) is 6 (1×2×3) and four factorial is 24. Six problems to solve each day may be manageable while 24 may be overwhelming.”

The logic: You need enough variation (three regions with different challenges) to learn and test adaptations quickly. But not so much variation that you can’t respond to problems effectively. Once you’ve solved problems in the transformation zone, add the next cohort. We see this in management cybernetics with Ashby’s Law of Requisite Variety.

How change supposedly works - “behaving a path”:

Here’s the mechanism they’re testing: “There really is no a priori way to ‘analyze a path’ to system change. However, there is a way to ‘behave a path’ to transformative system change.”

You can’t plan complex system change in advance because you don’t know which parts will resist or how they’ll interact. But you can disturb the system by trying to change it, observe what happens, and respond.

The paper describes this: “As implementation teams are developed and include members of various departments who have not traditionally worked together, previous ways of work are threatened... The results of those disturbances reveal apparent and previously unknown connections and lack of connections among system components. Previously unknown proponents and detractors suddenly appear... As soon as the reactions are known, actual facilitators can be strengthened and relevant impediments can be resolved.”

They call this “practice-policy communication cycle” - implementation teams at regional and district levels attempt to implement, encounter barriers (lack of resources, conflicting policies, unclear authority), surface those problems to state leadership, who then modify policies and resources.

If this mechanism works as described, it would explain why Mississippi succeeded. They discovered and resolved implementation barriers over a decade rather than mandating a solution upfront and wondering why it didn’t work.

Whether it actually works that way, we can’t tell from this paper. They describe the theory but don’t document specific examples - like a barrier that surfaced through regional teams, the state policy that changed in response, and the implementation that improved as a result.

What the Evidence Actually Shows

The paper explicitly states it’s testing three predictions. Let’s assess each:

Prediction 1: “Purposeful development of implementation capacity is possible in complex state education systems”

What they showed: All Study 2 states improved from 20-40% baseline to 60-75% within 24 months with intensive support. The State Capacity Assessment administered repeatedly showed consistent improvement.

Meaning: Organizational capacity metrics improved with intensive support across different state contexts.

What we don’t know: Whether this organizational capacity enabled better implementation of educational practices or improved student learning. The paper doesn’t measure student outcomes or list what was being implemented.

That’s a limitation but not necessarily disqualifying. If you’re testing whether organizational capacity can be built at all, demonstrating it can be built is the first step. Connecting it to outcomes is the next step.

Prediction 2: “Purposeful capacity development can be replicated across departments of education in states that are unique in terms of history, size, and operations”

What they showed: Study 2 states ranged from 8 to 56 regions and 175 to 590 districts across Western, Midwestern, and Northeastern US. All showed similar improvement trajectories.

Meaning: Success appeared more replicable in Study 2 than Study 1, suggesting the refined approach worked across different contexts.

What we don’t know: Whether this replicates without intensive AIRN support. All successful states had monthly consulting visits over years. Can capacity develop without that level of external support? The paper doesn’t track what happens after AIRN leaves.

Prediction 3: “Repeated assessments of state capacity development can be conducted in education”

What they showed: The SCA was administered 2-6 times per state over multiple years with consistent data collection.

Meaning: They clearly demonstrated repeated assessment is feasible in education systems.

Caveat: The assessment was developed and administered by the intervention team, scored by participant consensus, with no independent validation. That creates potential for bias. But the 5-year data from Study 1 suggests repeated testing probably didn’t artificially inflate scores (some states showed no progress despite repeated assessment).

The Cost Question

The paper describes implementation capacity development as “nearly cost-neutral” because states “repurposed” existing staff.

What was repurposed:

• State education staff became State Transformation Specialists

• Regional staff formed Regional Implementation Teams

• Staff time reallocated from previous duties to implementation roles

What this doesn’t include:

• AIRN consultant fees for monthly site visits over years

• Federal contract funding

• Opportunity costs of staff time reallocation

Someone funded the consultants. I can’t figure out from this paper what building implementation capacity actually costs. That matters for scaling.

The context they provide:

Failed reforms with poor implementation:

• Comprehensive School Reform: $2+ billion, 8,000 schools, no impact

• School Improvement Grants: $3+ billion, no significant outcomes

• Common Core: $15.8 billion estimated state costs, no measurable improvement

If implementation infrastructure prevents wasting billions on failed reforms, even substantial investment could be rational. Mississippi invested heavily in literacy coaches. Alabama’s Numeracy Act invested $114 million annually in math coaches. DoD schools pay teachers $88,000 versus $31,900 in some states.

Improvement isn’t free. But transparency about costs helps assess feasibility.

The Mississippi Connection

The framework AIRN developed sort of sound like what Mississippi actually built during their reading reforms (2013-2023):

• Literacy coaches in every school

• Multi-year sustained teacher training programs

• Individual student reading plans for systematic tracking

• Third-grade retention with extensive intervention

• Stable leadership committed for a decade

This is exactly the host system infrastructure the paper describes. Mississippi didn’t just adopt phonics curricula but built comprehensive implementation capacity.

Why other states with similar policies got smaller results:

The paper’s explanation would be that other states didn’t fully build out host systems (at best), but most likely remained ghost systems. They had policies requiring phonics instruction and literacy coaches on paper but lacked the implementation infrastructure to ensure fidelity.

Researcher Matt Barnum noted (in broader context, not this paper) that other states adopted sixteen of the same policy recommendations as Mississippi including phonics training and retention policies, yet saw gains of only 4-5 points compared to Mississippi’s 10-point jump.

This helps reinforce what the paper suggests: implementation quality matters as much as what you implement. Quality is “difficult to codify in policy checklists.”

The unanswered question:

The similarities are interesting. Mississippi built host system capacity and measured student outcomes throughout. AIRN built organizational capacity metrics but didn’t track whether states where implementing similar things and whenever students learned more.

Questions This Leaves Unresolved

After working through this paper, several questions remain:

About mechanism: The practice-policy feedback cycle sounds promising in theory. But I’d like to see specific examples documented. Show me a concrete barrier that surfaced through regional teams, the specific state policy that changed in response, and measurable improvement in implementation as a result. That would make the theory tangible rather than abstract.

About measurement: The SCA tracks organizational changes: teams exist, meetings happen, documents get written. That’s capacity to have implementation infrastructure. But is that the same as capacity to actually implement practices with fidelity?

Mississippi had organizational infrastructure AND measured implementation fidelity of reading instruction AND tracked student reading outcomes. This paper measured the first part without connecting to the other two.

About sustainability: Study 2 worked better than Study 1. That’s legitimate learning. But all successful states had intensive monthly consulting support. What happens when that ends? One state saw work collapse after leadership change. If capacity requires permanent external support, that changes what “capacity building” means.

About standardization: The paper argues repeatedly against standardization while promoting Active Implementation Frameworks™ (note the trademark) with a State Capacity Development Plan that guides work month-by-month for 36 months.

Maybe that’s not a contradiction. Maybe the framework provides structure for local adaptation without becoming rigid. But every failed reform thought it was flexible too. How does this one avoid becoming the next standardized solution that fails for the reasons the paper identifies?

About the “ways of work” claim: The paper says implementation teams “change their ‘ways of work’ to increase organizational capacity.” This means changing how the organization functions, not just adding programs. Repurposing staff into implementation team roles. Changing meeting structures to include feedback loops. Modifying data systems to track fidelity, not just outcomes. Shifting from one-off workshops to sustained coaching.

That’s organizational transformation. But the paper describes this more than documents it. What specific organizational routines changed? How did day-to-day work differ before and after? The theory makes sense but the concrete examples would strengthen it.

What This Tells Us About Implementation

The paper addresses a real problem: we know many interventions that work in controlled settings but fail at scale. Understanding how to build implementation capacity systematically could matter.

The genuine contributions:

The failure analysis from Study 1 is valuable even if you’re skeptical about the broader framework. External consultants without system access fail. Segregated specialists without authority fail. Weak regional infrastructure predicts failure. Lack of executive commitment stalls progress.

These are specific, avoidable mistakes with decent evidence behind them, especially considering the history of education consultants.

The theoretical framework can explain things and can back up claims to a degree. The complexity science perspective (also known as Ashby’s Law) (that systems need internal flexibility to match external complexity) explains why standardized reforms fail. The ghost system vs host system distinction clarifies what’s missing in most reform efforts.

The subscale sequence data suggests implementation capacity develops in stages: leadership enables regional development, which enables system alignment. If that holds across contexts, it tells us something about how to sequence capacity building.

What would strengthen this:

The obvious next step: Connect capacity to outcomes. This is feasible retrospectively. Go back to those 10 states, get the NAEP data and graduation rates from the years they worked with them. Analyze whether higher-capacity states showed better student outcomes.

If higher capacity correlates with better outcomes, that validates the approach. If it doesn’t, that’s important to know too. Either way, connecting organizational capacity to educational results matters.

Additional evidence that would help: Independent assessment of capacity for one thing. Documentation of sustainability after intensive support ends. Detailed cost accounting including consultant fees and opportunity costs. Specific examples of the practice-policy feedback cycle working. Evidence that organizational capacity enables actual implementation fidelity.

The realistic assessment:

This represents serious work on a genuinely difficult problem. The researchers learned from initial failures and improved their methods. They documented organizational changes in complex systems with repeated measurement over a decade. They acknowledge limitations openly.

The evidence shows intensive consulting support can improve organizational capacity metrics across different state contexts. Whether this organizational capacity enables better educational implementation, and whether it persists without intensive support, remains unclear.

That doesn’t make the work worthless. It makes it incomplete. Both things can be true. We just need more work to find out, well, what works!

What this might explain about Mississippi:

The framework aligns with what Mississippi did: sustained infrastructure investment, literacy coaches, multi-year training, systematic implementation. Mississippi built host system capacity, not just ghost system policies.

But Mississippi also measured outcomes throughout. They knew literacy coaches were working because kids were reading better. This research measured organizational capacity without tracking whether education improved.

The alignment suggests the framework might explain part of Mississippi’s success. But it’s one piece of a larger puzzle that included measuring results and staying committed through an entire span of implementation.

Where This Leaves Us

Implementation capacity clearly matters. The graveyard of failed reforms exists because we focus on what to implement instead of how to implement. If someone has figured out how to build implementation capacity systematically, that would be significant progress.

This paper might be part of that solution. It’s developmental research (building and testing an approach) not proof the approach produces educational improvement. That’s legitimate work worth paying attention to.

It’s also incomplete in ways that matter for assessing whether this actually helps students learn more.

The specific lessons worth taking:

If you’re trying to build implementation capacity, the structural prerequisites from this paper seem well-supported. Embed specialists in the system with actual authority, not as external consultants. Secure executive commitment with regular meeting time before starting. Build regional partnerships with dedicated resources. Plan for sustained timelines measured in years. Start in transformation zones to learn before scaling. Measure progress and adjust based on data.

These align with what successful states like Mississippi and Alabama actually did.

What we still need to understand:

Does implementation capacity as measured here lead to better implementation of educational practices? Does it improve student learning (it really does depend on the curriculum!)? Can it be sustained without intensive consulting support? Can it scale beyond states with favorable conditions and substantial resources?

The paper addresses the first question in implementation science: can you purposefully build organizational capacity? The evidence suggests yes, with intensive support and the right conditions.

The second question (does that capacity improve education?) remains unanswered, but there are a number of reasons why like what’s being implemented is different!

Why I am a bit “verbose” on this:

Because implementation is where most reforms fail, and understanding how to build implementation capacity systematically would matter. This paper represents serious effort on that problem with evidence of learning from failures.

It’s also unfinished work. Organizational capacity tells us something about organizational development, but without, let’s say, a common set of curriculum or practices. Whether it tells us something about education improvement, this paper isn’t going to give you an answer, just clues to sniff out.

Both things are true. The work has value. The evidence is incomplete. It deserves attention and healthy skepticism.

People in the past was able to implement a lot of things without requiring the same support or costs as the paper suggest, but that was *decades* ago. I don’t think we need such fancy frameworks to achieve any sort of the same capacity, but to gain back any sort of similar capacity is going to cost a lot and will require support, especially as those who hawk “accountability” like 90s era GE Executives who later moved on to Boeing or some other storied now declining company (or worse Clinton admin alumni like Emanuel or Cuomo who are later reveled to be bad at governing) while ignoring Juran and Demings are swarming like vultures.

That’s where the evidence leaves us.

For more on implementation and quality management principles, Deming’s “Out of the Crisis” remains essential reading. He taught countries and companies alike how to build quality into systems through continuous improvement.

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Mississippi’s education reforms succeeded where Common Core rollout failed. The difference? I would guess that Mississippi owned its reforms, and they made sure they got implemented.

Now watch as the same factions that brought us Common Core prepare to bring their special touch, and the historical results we all know and love, to help “spread” the Miracle.

The Familiar Pattern

American education reform follows a predictable cycle: Local success story emerges. National media celebrates. Foundations fund “replication” (they call it replication, but somehow it never is). Congress mandates. Implementation fails. Parents wonder why Johnny can’t read. Reformers blame students and teachers. Repeat.

The Texas Miracle became No Child Left Behind. By 2011, Texas ranked 49th in verbal SAT scores. Common Core promised rigorous standards and delivered no measurable improvement while costing states an estimated $15.8 billion, but hey, at least the consulting fees were good. Now Mississippi rises from 49th to 9th in fourth-grade reading, and Alabama jumps from last to 32nd in fourth-grade math.

What many breathless accounts don’t mention, and something carefully inventoried, is the graveyard of previous miracles: KIPP’s 40% Black student attrition, Harlem Children’s Zone expelling an entire class for being “too weak to found a high school on,” DC charters expelling at 72x the rate of public schools, Bruce Randolph School’s 14% math proficiency after Obama’s 2011 praise, Pickett Middle’s “70% proficiency” collapsing to below district average.

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What We Know What Mississippi and Alabama Did

Mississippi didn’t adopt a miracle curriculum. Starting in 2013, they built comprehensive support systems over a decade:

• Mandatory teacher training in evidence-based reading instruction, not one-off workshops but sustained professional development

• Literacy coaches in schools providing ongoing support

• Individual reading plans tracking each struggling student

• Third-grade retention with extensive intervention

I would love to point out, that Mississippi isn’t the only one to achieve interesting results. The Alabama’s 2022 Numeracy Act invested $114 million annually in systematic support:

• One math coach per 500 students

• 60 minutes daily of focused instruction

• Summer camps for struggling students.

• Abandons Common Core for Math

Both states succeeded through sustained investment in improving systems and better resource allocation.

The Mississippi Mystery

simplifies it to “Select really excellent, high-quality curricula and aggressively teach teachers how to use those curricula instead of putting them through generic “skills” training that won’t impact their classroom practices much. Measure how well students, schools, and districts are doing and hold back kids who aren’t reading at the end of third grade.”

Here’s the problem with that analysis: Mississippi wasn’t the only state to implement phonics-based reading instruction, hold back students, train teachers etc. On a more robust analysis Chalkbeat’s Matt Barnum notes, other states adopted sixteen of ExcelinEd’s recommendations including science of reading training, retention policies, and parts that Piper seem to over look like literacy coaches, yet saw gains of only four to five points compared to Mississippi’s ten-point jump. Bear in mind, states should try to achieve all of ExcelinEd’s (a bit broad) recommendations as fast as they can. It’s that rather than, a very simplified stance that Piper presents, find out what is the best way to implement and be willing to take a piecemeal approach if it speeds up the process. It’s just that implementation is a bit more *difficult* than being sold.

The gains began in 2013, but the retention mandate didn’t apply until 2015. Mississippi also saw similar jumps in math, suggesting something beyond the reading law alone. Rachel Canter of Mississippi First hypothesizes it was the state’s focus on “aligning its standards, testing, and accountability system, and sticking with it for many years.” In other words, sustained implementation of multiple aligned reforms, not any single policy.

We still don’t fully understand why Mississippi outperformed other states with identical policies on paper. Was it the particular mix of leaders? The specific sequence of reforms? The state’s starting point? This uncertainty is itself instructive: implementation quality matters, and implementation quality is difficult to codify in policy checklists. It is the biggest X factor whenever a project succeeds or fails if everyone follows the same checklists.

I mean implementation isn’t just following a checklist. Who is going to train the teachers, will the teachers be paid or fired, How are you going to keep track, and thousands of little details, that adds up. Details that states like California haven’t been so good at, or even other red states like Oklahoma. One thing that might explains it is that southern states are close to each other, which makes it easier to cross pollinate leadership, staff and implementation methods with each other. It would explain part of the reason why implementing Mississippi reading and Alabama math programs might work. Maryland is putting that theory to the test by hiring Carey Wright, the former State Superintendent of Education for Mississippi and the leader responsible for the Miracle, to be its new State Superintendent of Schools

(on a personal note, it is great seeing people succeeding upwards, not just failing upwards)

Beyond Test Scores: Schools as Community Infrastructure

Not to mention, focusing solely on test scores misses what fellow Substacker identifies as schools’ deeper function: community infrastructure that shapes entire neighborhoods.

Schools host voting, provide childcare that enables employment, create networks where parents organize everything from little league to local politics. When districts made rapid, disruptive changes to teaching forces in the past, they didn’t just affect test scores, those changes affected the parents, the extended family, and the broader community. When charter networks expelled high percentages of struggling students, they didn’t just manipulate graduation rates, the charter schools created a period of uncertainty and disconnection as they remove families’ childcare, networks, and etc etc despite promising to be a better school.

This doesn’t mean test scores don’t matter. It means that sustainable improvement requires attention to schools’ multiple roles in community life.

Implementation Capacity vs. Policy Design

Many analyses of Mississippi’s success emphasize accountability measures like third-grade retention. But as education reporter Chad Aldeman noted, what matters isn’t the retention itself but how the policy changes adult behavior, forcing schools to “pull out all the stops” with assessment protocols, targeted tutoring, and intensive support.

“Accountability” measures grab headlines. Implementation capacity does the actual work. Mississippi succeeded because they spent a decade building infrastructure to ensure kids wouldn’t need to be held back. The literacy coaches, the sustained training, the individual reading plans: these are support systems, not “accountability” mechanisms. The goal is to get the kid to read, not punish them for not being able to read.

This distinction matters. Accountability without capacity is just blame-shifting. You can’t test your way to excellence any more than you can weigh yourself thin, though that won’t stop people from trying. Edward Deming taught that 94% of problems stem from systems, not individual choices. Making punishment or fear the driver of metrics leads to declining quality, whether in industry (consider Jack Welch’s legacy or Boeing’s recent failures) or education (the documented scandals where “choose excellence” reforms became choose-to-exclude-struggling-students operations).

Freddie deBoer again understood a basic concept of quality management that miracle-mongers miss: you can’t “accountability” your way to systemic improvement. DeBoer documented how every ‘choose excellence’ reform became a choose-to-exclude-struggling-students scandal. That variation is still an active force in the world. So far the evidence points to Mississippi and Alabama as exceptions to this trend, and if so it’s because of their ability to implement, considering other states have, on paper, met the same checkmarks but still didn’t achieve the same results.

Why Standardization Often Fails

America operates through 14,000 school districts across 50 state systems, with god knows how many school board members, superintendents, and principals. In operations research and quality management, we repeatedly see the principle that systems need internal flexibility to match external complexity.

Mississippi’s relatively homogeneous, politically stable environment enabled sustained focus. California’s diverse, dynamic context requires different approaches. Louisiana, Alabama, and Tennessee share certain characteristics that may not apply elsewhere. One size cannot fit all, though that’s never stopped reformers from trying.

The reformers pushing standardization often miss that Mississippi succeeded precisely because it was Mississippi doing it for Mississippi. They had stable political leadership, community buy-in, and sustained commitment. These conditions cannot be mandated from above, you gotta cultivate them locally. But that’s harder work than buying a curriculum package.

The Department of Defense Exception

Ironically, the highest-performing schools in America are the Department of Defense’s school system, demonstrating exactly why local system-building works. With 66,000 students, Pentagon schools outscored every state in math and reading. Black and Hispanic eighth-graders in DoD schools outperform white students nationally.

How? Through precisely what Mississippi and Alabama are doing: building comprehensive support systems. The New York Times reports that DoD teachers earn $88,000 versus $31,900 in some states (crazy right?). They have 10-15 years average experience. Supply closets are stocked. When DoD schools implemented their own Common Core-like standards in 2015, they took six years for methodical rollout with sustained training and support, not the rushed, underfunded implementation many states experienced.

DoD succeeds because it controls its entire system and can ensure adequate resources. As one DoD principal explained, the goal isn’t “pockets of excellence” but raising the floor for all students through systematic improvement.

Notably, I haven’t seen too many pundits talking about replicating DoD’s success. Wonder why? Perhaps because reformers want Mississippi’s test scores without Mississippi’s patience or DoD’s resources. Notice what they never propose: giving every school DoD-level funding, teacher salaries, and support staff.

There’s another wrinkle: Freddie deBoer would argue that the DoD has way more control over the context, like living arrangements and being their parents’ employers, than public schools. Fair enough, but considering how DoD schools seem to outperform most other states and considering military families are often at the lower end of the income spectrum, they are doing that 10% really really well.

The Singapore Paradox

Singapore succeeds through strong central planning impossible in our federal system. Singapore can mandate curriculum changes for its 360 schools overnight. Yet even in America, when districts try to implement Singapore Math, success depends entirely on implementation quality.

Research shows Singapore Math can produce positive impacts (effect sizes of 0.11-0.15 standard deviations) but only with substantial implementation investment. Districts that purchased textbooks without teacher training saw little improvement. Success requires multi-year professional development programs, deep understanding of methodology, administrative support, and assessment alignment.

In other words, Singapore Math works when districts build capacity to implement it properly, exactly what Mississippi did with reading instruction. The curriculum matters less than the system supporting it.

Potential Limitations

We should acknowledge some complications. In 2015, Mississippi aligned its state test more closely with NAEP. As testing expert Andrew Ho notes, “To the extent you prioritize NAEP, you risk inflating NAEP scores.” This isn’t necessarily gaming the system, but it adds nuance. The timing doesn’t fully explain the gains (which began in 2013), but it’s part of the picture.

Additionally, Mississippi’s gains could stall. Eighth-grade scores already show concerning patterns. New leadership could abandon literacy coaches. Budget cuts could eliminate support systems. This fragility isn’t a flaw in Mississippi’s approach: it’s inherent to continuous improvement. Quality requires constant attention, ongoing investment, and renewed commitment.

Building Capacity, Not Mandates

The path forward isn’t standardizing Mississippi’s approach but understanding why Mississippi succeeded where Common Core failed: local ownership, sustained implementation, and systematic support.

For education leaders genuinely committed to improvement, Mississippi proves you can succeed, but only with sustained community support, adequate resources, and critically, time.

States and localities need:

Implementation infrastructure: Not curriculum mandates but support for building local capacity: training programs, coaching systems, professional development.

Documentation without prescription: Share what worked without mandating rigid methods. Provide frameworks that allow local adaptation. (something we been working on personally with Textbook)

Sustained commitment: Recognition that real improvement takes years, often longer than election cycles. This requires political courage and community patience.

Resource adequacy: Mississippi and Alabama invested significantly in their successful programs. DoD schools spend generously. Improvement isn’t free.

The federal role should focus on providing resources and documenting successes, not mandating methods. Foundations should fund implementation capacity, not develop the next universal curriculum. States should focus on building support systems, not adopting the latest program.

The Difficult Question: What About Resistance?

This raises an uncomfortable question: What do we do about districts that refuse to build capacity?

There’s a crucial difference between implementations that fail despite genuine effort and leadership that refuses to implement improvements at all. Mississippi had leaders willing to stay the course for a decade. Some districts have leaders who won’t even acknowledge the need for improvement.

The former deserve support, resources, and patience. The latter require different interventions—potentially state oversight, leadership changes, or in extreme cases, restructuring. This is different from imposing standardized solutions; it’s addressing genuine failures of will or capacity.

We need clearer distinctions between:

• Places struggling to implement (need support)

• Places implementing the wrong things (need better information and flexibility to adapt)

• Places refusing to try (need leadership accountability)

Each requires different responses, and conflating them leads to both over-intervention and under-support.

The Real Goal: Schools Worth Attending

The goal shouldn’t be marginally boosting NAEP scores while crushing the joy of learning. We need schools that instill curiosity, build community, and prepare students for lives worth living, not just tests worth passing.

Schools aren’t test-score factories; they’re community infrastructure. They provide childcare that enables parents to work, create networks that strengthen civic life, offer gathering spaces for everything from voting to vaccination clinics. Schools determine whether neighborhoods get investment or abandonment, whether local businesses survive or shutter, whether communities have organizational capacity.

Mississippi and Alabama are building better schools for their communities: institutions where teachers are trained, students are challenged, and parents are welcomed. They’re creating educational institutions that serve their actual purpose: developing capable, curious human beings who can engage with complex ideas.

Maybe Freddie deBoer is right that, besides air quality and other environmental factors, there is a limit on what schools can do to improve relative test scores? So what! When talking about education, people miss how schools function as community institutions. School shutdowns didn’t just hurt students during COVID, but parents and the broader community. The goal is better schools and better integration with communities because it is a valuable thing to have.

The Choice Ahead

We can continue the cycle of miraculous discovery, standardization, failure, and abandonment that has characterized American education reform for forty years. Or we can do the harder work of building capacity: supporting local and state officials, investing in implementation infrastructure, and accepting that improvement happens through patient system-building, not revolutionary mandates.

This requires holding three things we know at time of writing:

First, Mississippi’s gains are real and matter with the current verification we have. When fourth-graders learn to read proficiently, that’s genuine progress worth celebrating and understanding. People on all sides of the debate keep forgetting that test scores and grading are useful as diagnostic tools.

Second, schools serve multiple functions beyond academic metrics. They provide community infrastructure, enable parental employment through childcare, create civic networks, and shape neighborhood vitality. Sustainable improvement requires attention to these roles, not just NAEP scores.

Third, there are structural limits to what schools alone can achieve. Freddie deBoer is maybe right that schools control perhaps 10% of variance in student outcomes, with socioeconomic factors driving most achievement gaps. I hold the stance that schools have more of an impaction, but even then with Freddie’s argument that this doesn’t mean schools can’t improve in the absolute sense, Mississippi proves they can, but it means we shouldn’t expect schools to single-handedly solve poverty-driven inequality. Especially considering we have high scoring Purdue students who can’t get a job at Chipotle. Before you go, blue collar jobs on me, manufacturing and blue collar jobs are also dying out, soooooooooooooo yeeeeeaaaaaah.

We can build better schools. We can improve reading instruction, math proficiency, and school climate (concrete, achievable, absolute goals). What we cannot do is replicate success through top-down mandates, expect identical results from different contexts, or close all achievement gaps through pedagogy alone. We should encourage the spread of what works, and we need to ramp up implementation capacity if we want the results. It’s not an either or, but a *very* difficult political and management problem. It’s made even worse, because a lot of false *miracles* that waste people’s time over and over.

The choice matters because it determines whether the next generation gets schools that work as schools and instill the joy of learning and reading - institutions that develop capable students, strengthen communities, and operate with adequate resources - or simply another cycle of disappointed promises chasing miraculous transformation that school systems were never designed to deliver.

On that note, We have a delightful little online handbook taking a look at all sorts of success cases if people are interested.

If you are wondering where to start with the idea of improving implementation ability, I would recommend reading the works to W. Edward Demings. I heard he did some good stuff with teaching basics of implementation and quality management and what not, just ask Japan.

To the pundits, foundations and consultants already packaging Mississippi’s ‘playbook’: You failed with Common Core, No Child Left Behind, etc etc for these exact reasons. Learn or get out of the way.

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Solutions to common challenges in schools implemented in some other school district. Not only school districts, but also in cities and towns and states. Not only in America but in non national governments around the world. Cities in China craft their own industrial policies. Towns in Japan test strategies for declining birthrates. Some of these towns now outperform not only their neighbors, but even parts of the United States. Mexican states run real-world experiments in economic development. This work matters.

This principle of small scale innovation has deep historical roots, even in national governments. from State Capacitance done great work on researching this stuff from WWII and the Cold War. The Truman/Eisenhower era US Government identified effective small-scale programs and scaled them into large government agencies. That was mostly the basics of Kaizen, incremental process improvement, work simplification (which I really need to finish up with Standards). Success cases are needed to show people that small to large improvements are possible.

This first prototype (of a prototype) of American Singapore(s) is Textbook, an Education Policy Guide. It compiles research and real-world case studies from U.S. school districts. This is a guide for parents, school board members, and/or other people who want better schools to have a better school.

Textbook

The Fragmentation Challenge

American public services operate is incredibly fragmented, especially the Greater Houston Area. Education in America alone involves approximately 14,000 school districts (with a wide variety in how they are managed) and 50 state education systems, each with distinct contexts, resources, and constraints. Housing policy varies by city, transportation planning occurs across jurisdictions, and family services operate through complex networks of local, state, and federal programs.

Despite this variation, national orgs and foundations promote standardized reforms as universal solutions (or school vouchers and try to ignore the issue all together). These initiatives originate from elite institutions, promise transformation, and assume implementation will follow from good design.

The track record suggests otherwise. Common Core State Standards, despite backing from some of the more wealthy states’ governors and hundreds of millions in foundation support, produced no clear improvement in student achievement. Technology initiatives have consumed billions while showing marginal impact.

Meanwhile, individual districts and states achieve meaningful improvements through careful implementation of evidence-based practices. Mississippi's systematic approach to reading instruction produced the nation's largest score gains over the past decade. North Carolina built a network of Early College High Schools that increase degree completion by tenfold. Various districts have addressed teacher shortages through housing programs, apprenticeship models, and partnerships with local colleges. These successes happen through sustained local effort rather than dramatic innovation, which may explain why they receive limited attention.

Guide Contents and Approach

The education guide examines policy areas that local and state leaders encounter: curriculum selection, student placement policies, teacher recruitment and retention, connections between K-12 and higher education, facility usage, technology adoption, reading instruction, and student support services. Each section synthesizes academic research while emphasizing real-world implementation.

Rather than promoting particular approaches, the guide documents what happened when districts implemented various policies. For instance, the section on Singapore Math explains that success depends on providing teachers with extensive training in the concrete-pictorial-abstract progression that underlies the curriculum. Districts that purchased textbooks without investing in professional development saw little improvement. Early College High Schools show remarkable success in rigorous studies, but only when strong partnerships exist between school districts and colleges to handle credit transfer, faculty credentials, and student support.

The guide distinguishes between programs with extensive evidence from studies, those with mixed or developing research bases, and popular approaches that lack supporting evidence or show potential harm.

This last category includes several promoted reforms. Detracking, the practice of eliminating advanced courses in favor of mixed-ability classrooms, has limited research support despite its popularity among equity advocates, who seem more than willing to pay a high political cost and needless antagonism for it. Studies suggest it may particularly harm high-achieving students from low-income families who depend on public schools for academic rigor. Online charter schools show concerning performance data, with lower test scores and graduation rates than traditional schools across states.

Systems Thinking in Education

This guide uses ideas from systems thinking to improve schools. I like to borrow ideas and thoughts from people like W. Edwards Deming and Stafford Beer.

Deming taught that most problems come from flawed systems, not flawed people. When schools struggle, people often blame teachers, students, or low level admins. But lasting improvement comes from changing the underlying structures and processes. Successful changes focus on redesigning systems rather than replacing people. You can't control greater powers, and there limits on how much you can compensate. You can make some changes that teachers or parents can't as a (local or state) school/education board member, principal, or superintendent.

Mississippi’s reading improvement success illustrates this idea. The state did not succeed by finding better teachers or students. Instead, it built a better system of support. This included mandatory teacher training in proven methods, literacy coaches in every school, aligned assessments, and sustained funding over many years. Other states tried similar curricula but did not build this full system, and saw little improvement.

Stafford Beer’s Law of Requisite Variety offers another key insight. It states that a system must have enough internal flexibility to respond to external complexity. Schools face tremendous variety in student needs, family backgrounds, and community conditions. Effective programs build in adaptability while maintaining high standards.

Community Schools offer a useful example. They integrate health services, extended learning time, and family outreach to meet diverse student needs. The specific services differ based on local priorities, but all use a coordinated structure to provide consistent support, and deal with the variation of students.

Implementation Patterns

Across different policy areas, successful implementations share common characteristics while failures follow predictable patterns.

Successful programs have clear theories of action linking activities to outcomes, strong feedback mechanisms to detect and address problems, adequate resources sustained over years, and adaptation strategies that preserve core components while adjusting to local contexts. Pretty cliche, I know, but it’s true.

Failures often result from incomplete adoption where districts visible elements while skipping essential supports. They lack feedback loops, so problems go undetected until damage is done. Resources prove insufficient for quality implementation, leading to diluted versions that don't produce intended effects. One-size-fits-all approaches ignore legitimate variation in local conditions and capacity.

The Early College High School model demonstrates successful implementation elements. These programs articulate how combining high school and college coursework leads to increased graduation and degree completion. They track student progress through both systems, identifying problems early. Successful programs secure stable funding that bridges K-12 and higher education streams. While maintaining core elements like formal partnerships and comprehensive support, they adapt to local workforce needs and student populations.

Current Status and Future Development

This prototype guide has significant limitations. Coverage focuses on selected policy areas where research and implementation examples are available. Some promising approaches lack documentation to include. Resource estimates come from available data but may not reflect all contexts. The guide represents an attempt to showcase why need to document, and why we need volunteers and help to create something more.

The vision extends beyond education to other domains where local implementation determines success. Housing guides could document how communities actually create affordable units despite zoning restrictions and financing challenges. Transportation guides could explain what works in adding transit service, bike infrastructure, and pedestrian improvements within typical budget constraints. Family service guides could synthesize effective models for childcare, elder care, and service integration.

Resource Requirements

Creating comprehensive practitioner guides requires sustained support that differs from typical research or advocacy funding (funding is needed thou). The work involves synthesizing existing research and verifying case studies rather than conducting new studies, documenting implementation experiences rather than running pilots, organizing knowledge for practitioners rather than academics, and maintaining resources over time rather than producing one-time reports.

This approach is a bit different from the nonprofit and foundation sectors, which favor innovation over documentation, breakthrough solutions over incremental improvement, new initiatives over sustaining existing work, etc etc.

Yet the need is clear. Thousands of local officials make consequential decisions with limited access to practical information about what has worked elsewhere under similar constraints.

The Bottomline

The education policy guide prototype is available at the button below. Feedback from practitioners will inform future development. The project seeks partners interested in developing similar resources across governance domains.

Textbook

The goal is not transforming American governance or competing with more centralized systems. Rather, it is providing useful information to the people working within existing structures to improve public services. Given the fragmented nature of American governance, improvement will continue happening community by community, district by district. These local leaders deserve access to the collective knowledge of their peers who have faced similar challenges. This prototype represents an initial attempt to provide that access.

"Universal Pre-K as Economic Stimulus," by Northwestern's C. Kirabo Jackson, Julia A. Turner, and Jacob Bastian, reveals UPK programs generate up to $20 in economic benefits for every dollar spent, dramatically lifting employment and labor force participation while potentially paying for themselves through increased tax revenue.

Why it matters: While UPK has long been proposed as economic stimulus, this first comprehensive analysis across nine states and cities provides clear evidence that accessible preschool programs drive substantial labor market gains beyond just helping parents of young children.

By the numbers:

• 1.2% increase in labor force participation

• 1.5% rise in employment rates

• 1.6% growth in hours worked

• $3-$20 generated in earnings for every dollar spent on UPK

• 10 percentage point increase in public Pre-K enrollment

• 5.5% growth in total real wages

Go deeper: Researchers analyzed Universal Pre-K programs implemented across Georgia, Oklahoma, West Virginia, Florida, Iowa, Wisconsin, D.C., Vermont, and New York City from 1995 to 2020, leveraging staggered adoption with a difference-in-differences approach:

• Enrollment impact: While some children shifted from private to public Pre-K (showing some crowd-out effect), overall enrollment rose 6.6 percentage points, with part-time enrollment increasing 3.6 points and full-time rising 3.7 points

• Employment pathways: UPK increased labor force participation by 0.8 percentage points and employment by 0.9 points, with the larger employment effect suggesting reduced unemployment and improved job matching

• Beyond parents: While mothers of young children experienced a 1.4 percentage point employment boost, they accounted for only one-third of total effects — indicating broader economic benefits

• Female focus: Women without young children showed substantial gains in full-time status (0.9 percentage points) and hours worked (0.28 weekly hours), while effects for prime-age men were minimal

• Multiple mechanisms: Effects operate through three channels: relieving informal caregivers (primarily women), increasing labor market attachment in anticipation of future childcare access, and boosting disposable income among families

• Time-use evidence: Using American Time Use Survey data, researchers found UPK reduced childcare time by 4.51 weekly hours for mothers of young children and 1.54 hours for women without young children

• Quality matters: Washington D.C.'s program — America's most ambitious, spending $22,207 per child — produced effects nearly double the national average with 1.7 percentage point increases in both labor force participation and employment

• Treatment heterogeneity: Effects varied substantially across locations, with the standard deviation of true effects estimated at 1.1 percentage points — explaining previously mixed research findings

• Inelastic labor demand: UPK had no effect on average wages despite increased labor supply, suggesting highly inelastic labor demand

• Self-financing potential: The employment boost generated enough tax revenue that UPK programs might fully pay for themselves through increased federal and state taxes

• Fiscal externality: Much of the tax revenue accrues to the federal government rather than states, highlighting the efficiency of federal subsidies for state UPK programs

Between the lines: Program quality and scale proved decisive. The researchers controlled for potentially confounding factors with region-by-year fixed effects and policy controls (EITC, minimum wages, welfare). Areas with higher public Pre-K enrollment and high-quality programming saw significantly stronger employment effects, while simply having a UPK program without substantial enrollment increases produced no measurable impact. That said, there isn’t much data in this study on simply *giving* parents the money directly vs Universal Pre-K.

A fundamental shift in how university inventions were handled after 1980 acted as a powerful magnet, drawing venture capital investment to specific regions and industries aligned with university research strengths, according to new research ("Innovation and capital" by Daniel C. Fehder, Naomi Hausman, and Yael V. Hochberg). This suggests focusing policy on boosting innovation supply might be more effective than just trying to attract capital directly.

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Why it matters

Venture capital is highly concentrated (e.g., top 3 cities got 60% of US VC in 2019), and policymakers often struggle to cultivate innovation hubs in other regions. This study explores whether boosting the supply of local, commercializable ideas is a key missing piece.

The 1980 Bayh-Dole Act dramatically changed the landscape for university research commercialization.

• Before: Ownership of inventions from federally-funded research (the majority of university research) typically rested with the government. Universities had weak incentives and faced hurdles (like negotiating individual agreements) to patent or license discoveries. Only about 5% of government-owned patents were licensed.

• After: Bayh-Dole gave universities the rights to own, patent, and keep royalties from inventions derived from federal funding. It required them to promote commercialization and share royalties with inventors, spurring the creation of Technology Transfer Offices (TTOs) and a surge in university patenting (from <300 in 1976 to >2000 by 1990).

The Setup: The study uses a difference-in-differences approach, leveraging a clever identification strategy. Since universities have diverse research specializations (e.g., UT Austin strong in engineering, Johns Hopkins in biosciences pre-1980), Bayh-Dole created varied shocks across regions and, critically, within regions across different industries based on the local university's pre-existing strengths. By comparing industries within the same county that were more vs. less related to the local university's expertise (using an "innovation index" based on pre-1980 university patent fields and industry relevance), researchers could isolate the impact of the innovation supply shock, controlling for broader geographic and industry trends using extensive fixed effects (County x Industry, County x Year, Industry x Year).

Data & Insights

The analysis tracks US patent data (NBER, USPTO, augmented with Gross & Sampat data), NSF federal funding records, and venture capital deals (from VentureXpert) at the county-industry-year level from 1970-1990.

• VC Follows University Innovation: Post-1980, VC funding, the number of deals, and the number of active investors systematically increased in geographic areas and specific industries most affected by the newly accessible university innovation. Event studies confirm these trends weren't apparent before 1980.

• A one standard deviation increase in a county-industry's pre-1980 university "innovation index" led to $109,000 more annual VC funding after 1980. This also corresponded to statistically significant increases in the number of local VC deals (+0.038) and active investors (+0.102).

• Looking at raw patent influence: each citation-weighted pre-1980 university patent corresponded to an increase of $45,000 in annual VC funding in that specific county-industry post-1980, plus related increases in deals (+0.016) and investors (+0.042).

• Elasticities: A 1% increase in the innovation index yielded a 2.7% to 3.9% increase in VC dollars, deals, and investors.

• Quantifying the Impact: The Bayh-Dole innovation shock appears to account for over 16% of the total increase in VC funding flowing into these university counties between the 1970s and 1990. (This rises to over 1/3 if the early 90s VC boom is included).

• Federal Funding as a Mechanism: The positive effect on VC was significantly stronger in areas where universities received more federal research funding before 1980 (triple-interaction model), supporting the idea that Bayh-Dole's impact was tied directly to unlocking this specific pool of federally funded research.

• Geographic Concentration: Effects were strongest in the university's home county, decaying significantly in adjacent counties and further out (tested up to 75 miles), consistent with the local nature of knowledge spillovers and known VC investment preferences (monitoring/advising ease).

• Local Conditions Matter: The positive impact of university innovation on VC attraction was amplified in counties that already had higher median incomes, more college graduates, larger populations, higher wages, greater urbanization, and larger average establishment sizes pre-1980, suggesting absorptive capacity matters.

• "Horse Race" Results: When comparing predictors of post-1980 VC flows, the university innovation index strongly and significantly predicted VC attraction. Indices measuring pre-existing VC activity levels (scaled by R&D, à la Kortum & Lerner) and pre-existing corporate patenting levels showed much weaker or insignificant predictive power in the same models. This suggests the new supply of university innovation was a primary driver, not just path dependence.

• Broader Innovation Spillovers: Beyond attracting VC, pre-1980 university innovation strength also significantly predicted where corporate patenting would increase after Bayh-Dole, even controlling for prior corporate patenting activity. This aligns with findings that government R&D can seed persistent clusters.

• High-Growth Entrepreneurship Link: Using Startup Cartography Project data (1988-1995), the study found university counties (especially those with high pre-1980 federal funding) had significantly more high-growth entrepreneurial activity (firms with eventual IPOs/acquisitions). Controlling for contemporary VC investment significantly reduced the direct statistical link between university innovation and entrepreneurship outcomes, suggesting VC acts as a key intermediary, identifying and funding promising ventures emerging from the university ecosystem.

Between the lines: The Bayh-Dole Act coincided with regulatory changes (like ERISA's "Prudent Man" rule clarification and Small Business Act changes favoring LPs) that significantly increased the total capital available to VC funds. This research shows that the supply of commercializable innovation from universities played a key role in directing where this influx of capital was deployed, towards regions and industries benefiting from the newly accessible frontier research, rather than solely reinforcing existing corporate strongholds or prior VC hubs.

My Notes

This research highlights an important sequence: Public funding generates research, and then policy choices, like the Bayh-Dole Act, fundamentally reshaped how these ideas became investment opportunities. Financial firms, particularly Venture Capital (VC), subsequently played a central role in directing investment towards these innovations.

Universities are key players here, they are underused tools to help boost local economies or specific industries. However, using them effectively for that purpose isn't easy; it takes more than just letting them patent inventions, as local conditions and planning matters.

The heavy reliance on VC funding also raises questions. VCs aim for big financial wins, which might not always line up with the public good goals behind the original research (like broad benefits or helping struggling regions). This makes it important to think about other ways to fund these new ideas, perhaps through different kinds of banks or investment funds focused more directly on public benefits.

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Today, I bring you an interview with Ryan Allen. Ryan Allen is a professor of international education at Soka University of America in Southern California and the author of the newsletter "College Towns," which explores the intersection of higher education and urbanism. Our conversation covers his transition from academic publishing to public writing, the challenges facing higher education, and how colleges can better integrate with their communities through thoughtful urban design.

Key points:

• The PhD trap: "We probably got to start telling people don't go do PhDs" — the job market has collapsed while universities keep churning out graduates destined for precarious employment.

• Universities as urban saviors: Colleges preserved walkable "pre-war" neighborhoods that would have been bulldozed for suburban sprawl elsewhere.

• Everyone loves universities except their neighbors: The persistent "town and gown" conflict sees locals fighting against student housing despite choosing to live near campuses.

• The common enemy isn't people—it's stagnation: Rather than fighting "NIMBYs," urbanists should unite against "freezing towns in amber and endless sprawl."

• Disney's $130 urbanism irony: Disneyland charges visitors to experience the walkable main streets that once existed naturally in every American town before suburban development destroyed them.

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Introduction & Background

Dave Deek: Hi Ryan, how are you doing?

Ryan Allen: Dave, doing well. Doing all right. It's not quite a sunny day here in Southern California, so I think I've been lied to with that PR campaign.

Dave Deek: At least it's not Houston where the weather just kind of been bipolar like it's hot and what you imagine Houston to be then it's suddenly cold and rainy and then go back to hot.

Ryan Allen: Sure. Yeah. I know we Southern Californians shouldn't complain, but we certainly do a lot.

Dave Deek: All right. But before we dive in, could you share what led you to write College Towns and what's your personal connection to both higher education and urbanism and YIMBYism?

Ryan Allen: Yeah, sure. I mean, the short story is I received tenure over the summer and I always said once I did get tenure, I was going to try to put more... I'm a professor. I guess I should say that I'm a professor at Soka University of America here in Southern California. I teach international education. And I've always thought that academic publishing is just not very fast. I just had an article that came out a couple days ago that literally it's five years in the making and it just gets bogged down with—I mean peer review is good, but other ways around the sort of the journal system isn't good. The book publishing can be very slow in academic presses.

So I just told myself if I get tenure, I'm gonna start kind of putting myself more out there, writing quickly because it's really hard to get things out there quickly in academia. So I was like, "All right, I can kind of do this myself." So that's kind of the quick story.

I think the longer story is I've always had kind of this passion for public intellectuals or sort of public writing. I mean, I thought maybe at one time I would be a journalist. I had a fork in the road moment of going to a PhD or going to be sort of a journalist with a publication in China. I decided to go do my PhD and even my undergrad background was PR communications which is not really in my area now but it's kind of helped me think about writing and presenting myself.

And then even when I told myself I was going to start College Towns I was hesitant. I think I started in October and I received tenure kind of over the summer. So it's a few months of me just kind of thinking should I really do this? Should I try to write op-eds in popular publications? And I did that. I started kind of trying to publish op-eds in newspapers, magazines, whatever it was and I had two rejections right in a row and I was just kind of annoyed. I was like, "Man, two different rejections, two different articles, two things I wanted to get out there" and it was one of those things like you write it and then as time goes on it can't really be published again. This is kind of a waste of time.

I'm going to keep putting in all this effort and then the things don't get published. So I said, what, I'm just going to start this urbanism and sort of education together. And I love the idea of college towns. I'm passionate about higher ed, but just the college itself. I mean, that's where I wanted to work. My first job out of undergrad, I was a leadership consultant for my fraternity's headquarters. I would travel across the country going to different college campuses sort of helping the chapters or sometimes they would get in trouble because 20-year-old dudes do a lot of dumb stuff. So I got to see these campuses across the country and really was just an amazing experience and so I kind of chased that professionally.

And so I have an academic background in higher ed, but in terms of that urbanism, that's always kind of been a part of my life, sort of personally rather than professionally. Studying abroad in Italy kind of inspired me to think more along those things. And on Twitter actually is where I really started getting big into these kind of movements, connecting with Strong Towns. I end up writing for them a little bit, at least one article. And so I said, "This is actually much more interesting and important. People are caring about this than my other academic areas." And so I'm welding them together now in College Towns.

And so I'm writing a book and putting some work from the book there and connecting sort of aspects of town and gown and these types of things and it's been a lot of fun.

College Towns

College Towns, where urbanism meets higher education.

By Ryan M Allen

Faculty Working Conditions & PhD Education

Dave Deek: That sounds a lot of fun and I really do appreciate when professors decide to write directly more often. I've been reading and summarizing a whole lot of academic papers and besides the fact they're academic papers, there's actually a few good ones and a few of the professors who write them, the research students that write them, they just stick with publishing out papers. They don't have to elaborate, explain their thought process why they decide to research more often than not. And I really do appreciate when professors decide to write more, but I need to make sure that I don't get us off topic.

Ryan Allen: Yeah, sorry if I went a little derailed there.

Dave Deek: No. No. You can get derailed. You're the one being interviewed. I should be the one that should stick to the topic.

Ryan Allen: Okay, fair enough.

Dave Deek: So, let's get to a number of your articles. When you covered that homeless professor I believe his name was Dr. Daniel McKeown and the school was UCLA, is that correct?

Ryan Allen: That's right. Yeah.

Dave Deek: What do you think about these? We're seeing more and more stories especially now with the Trump administration about faculty working conditions not just declining from the universities taking advantage of the faculty labor market but also because the Trump administration is putting the pressure on academia, especially what academics could say speech-wise, and what are your solutions to this growing problem, if there are solutions?

Ryan Allen: Yeah. I mean, that interview even happened before Trump was elected so I hesitate to blame everything on Trump or even most of the things that are happening in our sector. It's sort of a long tale of 40 years of changes in higher education.

And in his case in particular, he had kind of been dangled—you go into a PhD program and often times they're training you for academia on the other side. That's what our programs are often training for, but the reality is there's just not as many jobs as they're allowing into these PhD programs.

And what ends up happening, a lot of people just go and they leave and that's fine. They're like, "Great, I got some skills, I got a PhD and now I'm happy in another sector" and we actually call that alt-academia even though that's what a lot of people are going to do, to be honest, more so than in actual academia. But he was one of these guys that sort of loved teaching and really saw himself as a professor. And so he got kind of—I don't want to say trapped but sort of funneled into what I call "adjunctification," although he kind of pushed back when I called it that. But essentially precarious jobs that don't pay much. From the outside it might seem really cool—"I'm a professor at UCLA" but what does that mean?

It's like, okay, I'm teaching 150 students per class and I am making 60 grand a year or whatever it was, maybe less in some cases. And there's just so many jobs like that. He's in some ways lucky. Sometimes you might get a job that's just giving you one class. So it's four grand for the semester. That's just like a basic adjunct job. He actually was a lecturer, sort of technically a full-time position, but it's this kind of package of positions that universities are doing due to budget cuts due to kind of just not—when they invest in a faculty who's going to be tenured, that's a huge commitment because we're there for 20, 30, whatever even longer years.

So I always tell people—like you said, how can we fix this problem?—we probably got to start telling people don't go do PhDs. Like I'm sorry, it might be your passion but the careers just aren't there. It's six or more years of your life where you're basically not really working. So I always hesitate to tell my students "you got to know what's on the other side for this." It's not just "okay I am going to this position and they're going to be paying me." Now they have PhDs that don't even fund and you pay them for six years of your time. And this is just not a development that I think a lot of people are ready for and then once they get into it, it's sort of like they feel like "I've already invested this much into it, now I can't quit now." And so you just sort of get funneled into these positions.

So I always tell people don't go do a PhD. Of course some people want to do it and that's fine. But we have to make it clear what's going to happen on the other side. How to fix that? I mean that's like a broader argument about fixing higher ed and properly funding higher education, going back to some kind of teaching focused, putting respect on people who are teachers. I don't think it's happening anytime soon because the direction that we're going is the opposite with some of the things that are happening with the Trump administration where they're cutting X, Y, and Z and we're in a big battle now.

So it's like the sector already had its issues. We have this new problem that I honestly don't really... I mean maybe you're going to ask me but I'm not quite sure how to exactly grapple with it. But at least right now I think telling people not to go to PhDs unless they have either independently wealthy or they don't really care if they're not going to be an academic and maybe they're an international student they just want to stay in the country... although again there's issues with that now. So that's kind of my take on my own field.

US vs. China Higher Education Landscape

Dave Deek: That's very—how do I say here?—not very fun to think about, especially considering I believe you written an article about Deep Seek's AI team and their education backgrounds and challenging assumptions about universities overseas especially Chinese universities. With this in mind, with basically the decay of the American PhD, the American degree altogether, how do you see the landscape of higher education shifting especially between the US and China?

Ryan Allen: Yeah, I mean I guess in two ways. So the Deep Seek thing was interesting because I think a lot of people when they saw Deep Seek, there's an assumption that those students were trained in the United States and they went back and we lost them due to brain drain. And what I found is that wasn't true. They had pretty much but almost all of them had been trained from undergrad to their PhDs, although not all of them had PhDs, in Chinese universities. And so that's like "Wow. Okay, they don't need us anymore. They don't need our expertise."

The second aspect of that was even I went back and looked at their professors that they had listed and even those professors for the most part had been trained in China. So now we're two generations out of this really advanced research that's happening in Chinese universities—you're right that they don't need the United States.

I will clarify I think sometimes when I talk about this I'm talking about PhDs broadly and there really is a difference between STEM, where you're in a lab or where you're doing some sort of technical work, versus maybe the humanities or the social sciences. The humanities and social science—it can be done but it's difficult to translate that into work, whereas the technical ones—I mean you saw that some of those students in that article they were bridging pretty easily into companies like Deep Seek or even others like Nvidia. There were people who connected to that because they have those technical skills and they are wanted in these other sectors. So the STEM sector is a little bit different in terms of the PhD.

But again you can learn some of those skills without a PhD. You can get technical training or even just a masters, and some of those STEM skills are enough for undergrads or people drop out. I mean that's the big thing—like you go to Stanford and you drop out. I think I saw a meme or even social media viral post this week where it was like "you go to Stanford and you drop out the first day because you meet people to start your AI company." Now again that's not everybody but it is kind of funny to think about. There is a difference between these kind of STEM fields.

What I'll say is that I think the US sector can and still is strong. We keep hurting ourselves in terms of the decisions that are happening right now. But up until two months ago, we still attracted students from around the world. Even if Chinese universities were getting better, we're still getting some Chinese students. Obviously, we were getting a ton of Indian students. Indian students in the past couple years had surpassed Chinese students. So, that was really our competitive advantage—like we're recruiting these people. They're the best minds and we're able to keep them. Right now, I am questioning that kind of future as we move forward just simply because of the stuff with the Trump administration and international students.

Dave Deek: All right. So one last purely higher education question before we move on to more about urbanism and YIMBYism. I just have to ask this question because I remember in the past right before the 1990s even the 2000s, the United States and a bunch of Western European universities were a bit more practical. I mean the Dutch used to have their entire agricultural industrial policy, the best way I could call it, revolving around Wageningen University.

Ryan Allen: Yeah, I mean—

Dave Deek: What do you think caused that change from practicality to academic publishing and do you think that might be one of the causes towards the decline of the American PhD or American higher education which was strong, which is strongish, but led to that decline?

Ryan Allen: Yeah, a couple things. First, the German, Dutch, some of the continental European systems are a little more practical. They have a kind of—I guess I can call it sort of like an academic type of practitioner kind of mentorship programs that are a little bit different than the American university and maybe the Anglo university. So they've always been a little more practical than our system. So that wouldn't be a surprise and I still believe they are that way with their technical track that isn't necessarily academic, although it's sort of welded to an academic system different than what we would consider kind of vocational ed in the United States. But I will say I'm not an expert on European higher education.

The second part of that and talking about our own is that I guess I would push back on the notion that the American system was more practical. I think it was actually less practical, and the problem is that we overproduced PhDs. So now there's all these programs and universities that are producing PhDs. There's just not enough spots. And so part of that is competition. So you have to now produce more papers for a PhD to get a graduate, to get a job—now they basically have to be as good as someone that was tenurable 20 years ago. And so it's just a nature of so many people trying to go into the market.

We're also chasing incentives of like you said papers which sometimes those don't necessarily help you or sorry maybe those don't have actual important information in them. It's just sort of like "okay I'm getting this out into the world because I need something checked off on my CV." That's not every academic paper but that's one of my critiques of the academic publishing space.

I'll also say I think in some ways chasing practicality has been a modern obsession with American universities. And when we were 40 years ago or even let's say when the GIs came out of World War II, we had the GI Bill, we really expanded higher education, the boomers came along—we weren't necessarily talking about job readiness per se or not in the same way we were. It was sort of universities had more of that liberal arts sense. The Soviet model was looking at work forces and this type of thing. Their universities were more focused on that. We were more focused on getting people in, having them think critically, have them just sort of a place to stay for a couple years, find themselves, understand, and then go out into the world. And I think that's when our universities at our best is when we're doing that.

It's when people can really find their passion, when they're not being sort of funneled into a thing because it's for work. The problem is the way that we now fund students or students have to fund themselves, then it starts breaking down into, "I'm getting saddled with $100,000 in debt just to go think for a couple years. It's no longer worth it." And so then we have to sort of say, "All right, what job do they get? If I'm going into debt 100K, I need a job on the other end."

And so that's where the real problem is coming from. Where I think if we can sort of get away from that debt, it would be better if we go back to that kind of more liberal arts model where it's not about the job, it's about just thinking for four years.

Dave Deek: Okay, that sounds very familiar with the argument I read. I think it was W. Edwards Deming, I believe the industrial engineer who was arguing actually a lot of the same points you are, I believe in his book "The New Economics," and he was arguing that education should be more about learning critical thinking stuff like that here because systems are going to change, systems going to adapt, etc., etc., right? But I need to make sure I get back on topic here.

College-Community Relationships & Urbanism

Dave Deek: Let's—that brings up another thought in my head. How do you see the ideal relationship between a college and its surrounding community? What examples have you found that demonstrate healthy integration especially on more of an urbanist vibe?

Ryan Allen: Yeah, I mean that's really like my love of college is the college town. And so one thing that I really appreciate—and I'll probably have an article about this soon—is that in the United States system for colleges, we have colleges in the middle of Manhattan, like Columbia where I went, or in the middle of nowhere—I don't know, let's just throw out Stillwater, Oklahoma. And they're dotting the country to suburban.

And it's really one of the true kind of national egalitarian systems where we don't—now a lot of the old universities are sort of centered on the east coast but there's great universities in Georgia, there's great universities in Texas, there's great universities really in every single state and that was a purposeful investment by the American government in terms of land grant universities and private institutions like churches and things like that that establish these places.

And you see in a lot of towns and cities even that a university was built—and we're talking 100 years ago or more—and then slowly kind of incrementally everything around the university starts to build up because it's not just the students who are attracted to that space. It's sort of businesses. It's regular people. It's nice to live next to a university.

And so a lot of the best urbanism that we can see in some of the small towns too come from university towns or areas around a university because they sort of act as a natural city because a lot of students are living right on campus. They often don't have a car and so they've been able to preserve some of those pre-war structures that often got knocked down when suburban development became the dominant way that the United States was kind of building. But around the university because they sort of kept—because there was always students there, because you couldn't really sprawl students out (you can but it's a little bit more difficult or a little more complicated than with single families)—it kept those structures around campus.

And so, my love for this is everywhere I go, I find places that keep that old world charm or that pre-World War II charm simply by the nature of what a university is. It's essentially a small city and everything around the city is operating within that. There's obviously problems we can get into but that's kind of my rosy picture of universities and how they act as a development model essentially.

Housing Struggles and Solutions

Dave Deek: Speaking about rosy pictures, you documented a lot of the housing struggles from multiple angles, from the homeless professor that you interviewed to the student housing shortages. It seems to me that a lot of the businesses and a lot of the people that move into the college towns full-time and right are often the same kind of people arguing to restrict student housing, especially the whole "people pollution" thing.

Ryan Allen: Yeah, you're just making me laugh, but yes.

Dave Deek: I mean, I was about to ask you how do you view the irony and what solutions appear most promising to you?

Ryan Allen: Yeah. I mean it's tough because I often ask this question—why do you live next to a university if you hate universities and students? I don't understand. And let me be clear, it's not everybody, but I think we see this in the urbanism space where there's a subset group that is loud and that has time to go down to the city council. I think most people are just trying to live their lives. They don't really care if the university does X, Y, and Z. They enjoy living there.

And so I wouldn't categorize it as literally every single person living next to the university. That being said, we see this dynamic happen pretty much in every college town. There's even a term for it, "town and gown." I almost called the substack "Town and Gown," but I decided to go with "College Town" because it just sounded like a better name.

Anyways, this town and gown dynamic is often—okay, the university has some kind of dispute with the locals. And I'll say, I used to live in a pretty traditional college town in Orange, California, right next to my university. And I would see 20-year-olds, like I said, do stupid stuff. And they would run down the street at 2 in the morning screaming, chugging a beer or whatever. I saw that. And my neighbors, who are fine with the university, fine with anything that's happening, they would get angry. They would come to me and say, "Hey, Professor Allen, what's going on?" and I would have to send them over to—there's always a university kind of relations person making sure students aren't doing these types of things.

I think one of the problems—and trying to convey this to the town is difficult—but I think one of the solutions is building more on-campus housing. And often campus housing gets fought because the locals say it's going to be too tall. I always see that it's "too tall of a building" and you look around and it's like, "okay there's another building right across the street that's basically the same height."

"There's going to be too much traffic if these students live here." It's like the students can literally walk. We don't actually need much parking. But of course then you say that, and they say "okay now we got to build more parking because it's going to create more problems." And it's always these kinds of excuses.

But I think if we can build more campus housing, that stops students from living out in the houses that would be rented by people that aren't related to the university. And so that can help with rents and cost of housing that are outside of the campus space. It's just that we have to convince the locals that this is going to be better for them. And that is really difficult.

And if we can't convince them, in most cases, to be quite honest, we should just go ahead and build it if we have the right and figure out the consequences later. I know it's better, you want to have a good neighbor. But sometimes it just becomes unreasonable.

I covered this case in Lubbock, Texas, and Texas Tech, and literally the university had a stroad in front of it. Lubbock doesn't have the best urbanism and Texas Tech doesn't either. I sort of feel bad for the college. But anyways, they were trying to build this kind of campus housing right across the stroad from the entrance of the university and everyone was getting upset. The university apparently is going to go through with it. But the point being is that the problem isn't the kids. The problem is the road that's in between the university and these housings. It's a high-speed stroad. But I mean, it looks like a highway drag strip and it's literally between a neighborhood and the university. It doesn't make any sense to me. And we sort of have to convey that and talk about those things, I think.

Dave Deek: Yeah, that does not sound like a good idea, especially the fact that students tend to do weird stuff, but housing still needs to be built. So, I guess it balances out in that weird way.

Ryan Allen: Right. Yes.

Dave Deek: Besides talking about weird ways, I think I remember reading an article of yours that was talking about that students can handle smaller or weirder spaces, I think especially office hours and conversions. Could you talk more about that and how might colleges leverage that?

Ryan Allen: Yeah. This is something that I've gotten a lot of push back on. I always say that in urbanism we have all these regulations in land use and there's lot size minimums, room size, windows, there's all these type of restrictions and the idea is that we don't want to send somebody to live in a slum. That's the argument. Okay. And I get that. I understand that.

But our pendulum has swung too far and the American kind of conception of what a home has swung too big and so we're cutting out a lot of smaller housing units like the SRO (single room occupancy) which was a huge part of our cities 70 years ago, even more years ago. Young people or people moving to the city just trying to make their way, maybe some people who are trying to get back on their feet—we've essentially cut those out of our cities. We've either made them illegal and then when they shut down or they convert to hotels, this option doesn't exist anymore.

So what that does is without these kind of tinier spaces, it sends people to have roommates, to have somebody sleeping on the couch. That's what happens in these college towns—the students get crammed into a single family home in a neighborhood and they'll put two guys in one room and one guy's living on the couch or in the garage or something weird. Why? Because there's not these sort of tiny spaces that we used to have and that they're still around, especially if they're kind of grandfathered in. And students are happy to live there. They do all the time.

University dorms are exactly that. You have a little tiny room. Maybe you share it with somebody. You have a shared bathroom outside. And students don't mind living in the dorms. In fact, you can see it in the conversations with students. They would rather have a very tiny room that's their own space that they don't share with somebody, where they have their bed and their TV and their clothes and maybe a shared kitchen or whatever. They would rather have that than sleeping in a bigger room with somebody else in the same room. But due to some rules, we can't build these types of things. And it's cut out of an option.

I used to live in one in South Korea. Very tiny space. I mean, we're talking about less than 200 square feet or something like that. It was basically just a bed and I had a shower in mine which is kind of interesting—my bed bucked up against the shower and I really just lived there for a semester before I was able to move to a normal apartment with a couple dudes. And so that's the kind of thing that I think we need to start rethinking.

And again, I did mention I think in Boston, Mayor Wu has added universities into office conversion. And because offices are sort of often weird spaces with—windows might be an issue, of course it should be safe—but creating some kind of triangular room where the window is here and you have this weird space in the back. Students don't care. They're not a family. They're not going to live there permanently. They're going to live there for a year, semester, couple years, whatever, and then they're going to move out, but they need sort of this transition type space and office conversions can be—they're already a challenge. So, let's try this for students.

So that's something that really a lot of people push back on and they say—I've had people say "I like all of your writing except when you say that because I don't want people to go to slums" and they think that we're going to send all the poor people into these types of terrible housing situations like they see these pictures of Hong Kong or something. And I don't think that's what's going to happen and I would rather have people in smaller homes or tiny rooms rather than living on the street, rather than living in their car, rather than having to sleep on the couch or whatever. I would rather have that, and those are the options that we're facing right now.

Dave Deek: But I'm shocked that you get a lot of push back for this because we have two models of that in the past. We had these old YMCA building places which have small rooms just to give young men a place to stay on their own. It's even in the song YMCA...

Ryan Allen: Yeah. Right.

Dave Deek: And then the second modern example is where storefronts are being converted into net cafes in Japan. And while there's a lot of moralizing about it, these net cafes again you have private rooms with sleepable couches in there. It helps young people at least have a place to stay and deals with the law and helps a lot of lower income or young people as you said who just want their own space. And for you to get push back to me is just absurd.

Ryan Allen: Yeah, I mean it is absurd. Even modern dorms—UCLA was trying to build a dorm on their campus and the dimensions were basically the same as the current dorms on campus and there was a lot of complaint, protest, and sort of basically the argument was "this is too small, it's inhumane for students." And how can it be inhumane when the dorms that they're already living in are that size and they're popular and people want to live there?

It is absurd. And for me, I mean, not everybody who's commenting on my articles, they're probably more sympathetic, but I do think there is a lot of obstructionism simply hiding in concern for students and those types of things, and they just would rather not have any building at all and they would want fewer students. I think in most of the arguments, especially in the real policy space, again, not necessarily my readers or people I engage with on Twitter, but those are often obstructionist when you talk about the real world that's out there.

Tom & Jerry's Backgrounds and Media

Dave Deek: And before we start talking about obstruction of the real world stuff, I want—let's talk a little bit about more fiction, because I can't believe there's someone else besides me who appreciates Tom and Jerry's backgrounds. Those are awesome. Especially a lot of older Hanna-Barbera and a lot of the older American cartoon backgrounds. My gosh. Why did we ever get rid of those?

Ryan Allen: Yeah, I mean I saw that—it wasn't mine. I did write about it, but I saw it on Twitter. It has a vibe. It's making me want to go back and watch a bunch of old cartoons. I was thinking about going back and watching some of the old Speedy Gonzalez and see how they portrayed the American Southwest. I think that that could be really interesting. So, yeah, that might be like a future project, but if anyone's listening or reading, definitely go watch that.

It's very moody and it reminds me—we often hear this conversation about American animation and Pixar was awesome. It was cool back in the day in the 90s and the early 2000s, but now it's kind of dominated the way that we do our cartoons and drawings and animation, and things have gotten very ugly. Everything looks like either a second rate Toy Story or Rick and Morty. And there's not as much kind of beautiful animation like you might see in Japan or from our own history, Tom and Jerry or whatever that might be.

Dave Deek: But I would push back about that. I believe I haven't watched the show itself, but I saw some background images from shows I think it's called Steven Universe and Bee and Puppy Cat. I believe that's what they're called, these gorgeous backgrounds with these beach towns and stuff like that.

Ryan Allen: Interesting. I don't see that. That maybe is my own bias or bubble. I need to go and look at that. I don't really engage with that media, I guess. Fair.

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Urbanism Movements and Divisions

Dave Deek: And so let's go talk about the real world and the ugliness stuff like that here. One of the things I've been noticing a lot here is that a lot of urban groups, a lot of these transit guys, they're constantly starting to infight more and more and more and more and more. And a lot of the YIMBY guys, not all of them, I'm a YIMBY myself, but a lot of these YIMBY guys are picking fights against—from what I see—are other groups that might be more sympathetic to urbanism. Do you have any thoughts on that matter? And bear in mind if you're uncomfortable talking about this or you just want to talk about this but want it cut out, those are both options.

Ryan Allen: No, I don't mind. I can see it certainly myself. I am in a fight—and I'll write an article on this—with fellow urbanists who I really like and they're doing great stuff over self-driving cars. I'm an advocate of self-driving cars. I think it's going to end up being great for society. But I understand the reservations and I've gotten into some debates with fellow urbanists and again I'll write some articles on that in the future.

So I recognize that when we say "urbanist" we don't even have a good word for it—whatever I just say sort of like "the movement" because there really isn't like one thing that unites everybody. There are kind of a set of principles or sort of loose—we understand that what we're doing now is bad but maybe we don't all agree on the same direction.

My biggest fear is that this movement of building housing, transit, things like that gets stuck on either side of the culture war—basically every other issue that we have in the United States. And right now it actually doesn't track onto the culture war. There are right NIMBYs, there are left NIMBYs, there are left YIMBYs, there are right YIMBYs. And so that I think is great because we can sort of pull from this broad political spectrum. Although on the other side there's sort of a unified push back against building housing, things like that.

I think for me when I talk about these things I often point back to Strong Towns, I'm a big Strong Towns guy and maybe I don't agree with 100% of everything that they do—Chuck Marohn kind of talks about. In fact, I think they're not mostly in favor of self-driving cars, although I have a goal of trying to convince Chuck one of these days. But the point being is like they are this smaller organization that have these national grassroot movements. They kind of reject the label YIMBY even though Chuck, the founder of this organization, would say, "Okay, 90% of the stuff we agree with, maybe 95, but here's kind of the fringes where we don't." And that does bring up a lot of arguments and debates.

And I remember a few months ago or maybe last year I saw Strong Towns' Chuck Marohn arguing with sort of some YIMBYs who I really like. I think Nolan Gray and a couple other people and I was like this is like my two dads arguing or whatever, something like that—mom and dad arguing—because I really respect both of the movements broadly even if we do have those disagreements. But I think trying not to simply fall back into the labels—and that's what Strong Towns does—is helpful to gain people who might be distrustful of whether this is kind of left or right and just saying no, this is Strong Towns. These are some basic principles. So I do appreciate that and I think it could be helpful to follow their lead there.

Dave Deek: Yeah. But we at the end of the day, we all have the same common enemy that whether we're urbanists or YIMBY or whatever we call ourselves, and that's the NIMBYs. Especially it seems to me that NIMBYs of all colors, they just—as if they snap fingers—they unite, they attack, they seem instinctively willing to organize more. And what the only commonality that I see from the NIMBYs is demographics which always tends to be upper income, more so older folks, but some younger folks who just want to make impact—good or bad—seems to be a good chunk of them part of the NIMBY movement. And it's weird because you have these groups sometimes even headed by former investment bankers, executives, or whatnot here walking side by side with young leftists or these weird conservatives.

Ryan Allen: It's—I mean when you say we all have the common enemy, again Strong Towns tries to push back on that and tries to say OK and try to understand why don't these people want it and how to make an argument. Now sometimes I think OK you can make the argument, you could be rational, and they're still not going to take it, and Strong Towns I think would say all right then figure out how to do it or whatnot. But yeah, I mean I think rather than saying the enemy is NIMBYs, I think the enemy is freezing our towns in amber and endless sprawl.

I think sort of—what I would say the movement, most people would agree with those two things whether it's Strong Towns, broader YIMBYs—freezing in amber and endless sprawl, those two things to me are the biggest issue. And if we can rein in some of those things in the United States, like a lot of the problems—it doesn't solve everything—I think that's another issue too is people will point to YIMBYs or even just like public transportation or sort of urbanists and say, "You can't solve this. If we do this, it doesn't solve that." And it's like, if we said that with literally everything, we would do nothing. Not everything has to be solved by this one project or not everything has to be solved by adding a bus lane or whatever. Sure, we're gonna have other problems, but we can't put everything on these. Again, it goes back to the obstructionist. It's just throwing as many things at the solution to stop it from happening.

Dave Deek: Okay, that's a very good definition of NIMBYism—basically freezing our towns and promoting endless sprawl. And I think that might be a good rallying point for the groups, which I hope so, but I don't know if they're ever going to agree upon even that.

And this second thing here—I know I agree with you that YIMBYism reform or whatever is not going to be the one-stop shop to fix all our problems. But at the same time, I keep seeing especially among the abundance people sort of treating it like that when reality is that a lot of towns—even though it's not going to solve all their problems or most of their problems or even 10% of their problems—implementing some reforms like ADU reform or loosening up the zoning enables greater and greater paths forward to resolve their other issues.

Ryan Allen: I mean, I think that's one of the problems here is—maybe it's cliché, like we're this massive country and we're really diverse, but it's certainly true in terms of the sort of YIMBY or let's just call it urbanism or whatever we're talking about here. They're very different needs.

And I think one of them is—and again I'll probably write about this—I have a word document on my computer with 200 article ideas and I only publish once a week, and new ones come every week, but one of them is talking about how YIMBYism from New York and San Francisco often cloud the national conversation. And so I think that happens sometimes where it's like, "What do we need in California? What do we need in New York" is very different than potentially what they are going to need in—again I always go back to my hometown or my home state—like Tulsa, Oklahoma. Those are different things in the rust belt where maybe they have good bones but they have abandoned—those principles. Two very, very different places and needs.

And I think the movement is big enough for both of us. It's just sometimes the arguments get kind of centered on New York or congested pricing and San Francisco or whatever's happening there and the rest of the country just kind of is forgotten. Again that's why I go to Strong Towns because it's in Brainerd, Minnesota and they often are looking at small towns in this space. And for me with college towns—and them by name are often small places, not as big places—but they're often doing really interesting stuff that we can take lessons from that might be broader applied than what's happening in maybe New York or San Francisco.

Disney, Miyazaki, and Urban Design

Dave Deek: And just to wrap up, I'm going to ask two questions because I would love to go more into detail about that. Maybe hopefully if you're interested, you come back for a future interview to talk more about this stuff. But the last two questions here: what do you think of the Walt Disney—I would even just say Walt Disney here because his brother is also responsible for trying to promote urbanism in his own sense like the Disney brothers urbanism, EPCOT and stuff like that here. And the second thing here, we've seen—not a de facto, that's the wrong word—we don't see guys like Miyazaki talk about urbanism but you could see the sheer amount of urbanism through his work and through his art and what does it mean for a living, breathing town. What are your thoughts on both those?

Ryan Allen: Yeah, I also have a Disney article on the docket that I don't know when it'll come out. I live very close to Disneyland here in Southern California. In fact, I used to live so close where I'd hear the fireworks every single night—a little bit further now.

But what's funny is that Disneyland has that kind of main street, that classic idea of what a city is. And Disney himself was inspired by his hometown and his wife's hometown—sort of these ideas of an idyllic version of a city or a town that was no longer existing. The post-war America was—even before post-war, they had started kind of ripping up, defunding these street car lines and gearing up for the automobile. So that was kind of already happening even though we sort of broadly label it post-war.

And so what's funny is he built this idyllic town, but the problem is it costs $120, $130, whatever it costs now—it just keeps going up—to go in and walk down this town. And that feeling used to be in every town across the country, that little area where it was safe to walk, where kids could run around, where there were small businesses, where there were little trinkets, where there was sort of civic pride.

And he tried to sort of create a Disneyfied version of that. But that used to exist everywhere, including the town that it is in, used to have this really nice little main street area and you can go back and look at old photos. I've done a tweet storm about it. And it had this great little downtown. What did they do? They knocked down the housing. Some of it was racial animus actually to Hispanics who were living in the area. Some of it was just related to California's appetite for sprawl. And so now when you go to that area, it's just these department stores. There's no urbanism. There's one maybe house that doesn't have setbacks. Everything else is really wide and it's a really unpleasant place to be. There's not that much good urbanism happening in Anaheim, but it used to have it, unless you go to Disneyland. That's where the good urbanism is, in Disney.

And it's just—I find it ironic that we had to recreate it and now we have to go pay for it when this was our normal standard for years. And I can see the relation to Miyazaki there too in some of his movies. I know you've written about that a little bit as well. And I think part of that is Miyazaki is tapping into full-blown nostalgia on a lot of the things that he's doing in terms of childhood and Japan and another era. And he's really focusing on Japan. He's not really focusing on western nostalgia even though again we can see a lot of meaning and messaging in his work and that's relatable to us.

But I think both of them, Disney and Miyazaki, tap into a nostalgia for structures and forms and society before modernization, before—whatever our societies look like. Japan looks very different now and I think they're doing a lot of good stuff. But it certainly is true that a city like Tokyo had absorbed all these areas that might have been idyllic countryside.

So it's different forms of urbanism certainly but they're both tapping in on the same type of nostalgia.

Dave Deek: Okay, I think this is a great place to wrap up the interview.

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Questions for the audience:

1. Have you lived in a college town? How did you experience the "town and gown" relationship - as a benefit to the community or a source of tension?

2. Would you accept living in a 200-square-foot apartment if it meant having your own private space at an affordable price? Or would you prefer a larger shared living arrangement?

3. Is the American PhD becoming obsolete? With countries like China developing their own academic excellence, and the job market for professors collapsing, should we be rethinking doctoral education?

4. What public spaces in your community charge admission that were once free? Are we increasingly creating "Disney versions" of what used to be naturally occurring public amenities?

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A GLO discussion paper (Returns to Education and Overeducation Risk: A Dynamic Model by Lorenzo Navarini and Dieter Verhaest) gives new insights into how overeducation affects wage returns to higher education. It challenges long-held assumptions about overinvestment in college degrees and gives us a more nuanced understanding of educational outcomes.

The big picture: Using rich Belgian data and a novel dynamic model, the researchers uncover complex relationships between educational attainment, overeducation, and wages that paint a more optimistic picture of higher education returns than previously thought.

Key findings:

• Overeducation causes persistent wage penalties:

  • Wage penalties represent reduced earnings for overeducated workers compared to adequately matched peers with the same education level.

  • 3-4% for upper secondary and bachelor's degrees at age 23, but the penalty for bachelor's degrees tends to fade by age 29

  • Increases to 8.7% for master's degrees by age 29

  • Suggests scarring effects of initial overeducation for some graduates

• These penalties don't necessarily translate to lower overall returns:

  • Bachelor's degrees reduce overeducation risk by ten percentage points compared to upper secondary degrees.

  • Master's degrees still provide substantial unconditional returns (10.6% at age 29) despite increased overeducation risk.

  • Upper secondary degrees show limited returns, partly due to increased overeducation risk (30 percentage point increase)

• Effects align with job polarization trends:

  • Obtaining a bachelor's degree (strangely) appears to be an effective strategy to avoid overeducation.

  • Challenges the notion that overeducation is primarily a problem among higher education graduates

• Overeducation contributes to heterogeneity in realized (ex-post) returns:

  • It was especially pronounced for master's degrees.

  • The culprit is most likely job market friction.

  • Some graduates experience negative realized returns despite positive expected returns.

• Substantial heterogeneity in both expected and realized returns to education:

  • Differences in overeducation probabilities reflect differences in expected returns.

  • Overeducation risk doesn't seem to reinforce this heterogeneity further.

Methodology:

• Developed a novel decomposition framework to assess overeducation's impact on wage returns more comprehensively

• Used a dynamic model of joint educational choices and labor market outcomes

• Estimated based on detailed longitudinal data about young people's careers in Belgium (SONAR data)

• Accounted for selection bias and unobserved heterogeneity using a finite mixture distribution

• Utilized counterfactual simulation strategies to estimate treatment effects

Between the lines:

This study challenges conventional wisdom about overeducation and educational policy. Rather than indicating inefficient educational policies, the findings suggest overeducation is more likely a result of labor market frictions.

Consequently, reducing investments in higher education may not be the answer to solving overeducation among young workers. In fact, the results indicate that widening access to bachelor's degree programs could be beneficial. Job hunting challenges and inefficiencies in the job market are the primary culprits behind overeducation, not an overinvestment in education.

The research reconfirmed that higher education is boosting productivity, but the job market's inefficiencies create painful uncertainty for graduates despite, well, being more productive. Maybe we shouldn't focus on curtailing educational opportunities, but improving job matching and HR practices.

Additional Context:

• The Belgian labor market is relatively rigid, which may affect the strength of overeducation penalties.

• Data covers individuals entering the labor market between 1994 and 2003, a period of documented job polarization.

• Belgium combines high public subsidization and low tuition fees with compulsory schooling until the age of 18

The bottom line: While overeducation can create wage penalties, obtaining a college degree is often an effective strategy to improve job prospects and earnings potential.